Recent advances in statistical energy analysis
NASA Technical Reports Server (NTRS)
Heron, K. H.
1992-01-01
Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.
Virkler, Kelly; Lednev, Igor K
2009-09-15
Forensic analysis has become one of the most growing areas of analytical chemistry in recent years. The ability to determine the species of origin of a body fluid sample is a very important and crucial part of a forensic investigation. We introduce here a new technique which utilizes a modern analytical method based on the combination of Raman spectroscopy and advanced statistics to analyze the composition of blood traces from different species. Near-infrared Raman spectroscopy (NIR) was used to analyze multiple dry samples of human, canine, and feline blood for the ultimate application to forensic species identification. All of the spectra were combined into a single data matrix, and the number of principle components that described the system was determined using multiple statistical methods such as significant factor analysis (SFA), principle component analysis (PCA), and several cross-validation methods. Of the six principle components that were determined to be present, the first three, which contributed over 90% to the spectral data of the system, were used to form a three-dimensional scores plot that clearly showed significant separation between the three groups of species. Ellipsoids representing a 99% confidence interval surrounding each species group showed no overlap. This technique using Raman spectroscopy is nondestructive and quick and can potentially be performed at the scene of a crime.
Advanced statistical methods for improved data analysis of NASA astrophysics missions
NASA Astrophysics Data System (ADS)
Feigelson, Eric D.
The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.
Advanced statistical methods for improved data analysis of NASA astrophysics missions
NASA Technical Reports Server (NTRS)
Feigelson, Eric D.
1992-01-01
The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.
Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods
NASA Technical Reports Server (NTRS)
Green, Lawrence L.; Maxwell, Katherine A.; Glass, David E.; Vaughn, Wallace L.; Barger, Weston; Cook, Mylan
2016-01-01
The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.
Mathematical and statistical analysis
NASA Technical Reports Server (NTRS)
Houston, A. Glen
1988-01-01
The goal of the mathematical and statistical analysis component of RICIS is to research, develop, and evaluate mathematical and statistical techniques for aerospace technology applications. Specific research areas of interest include modeling, simulation, experiment design, reliability assessment, and numerical analysis.
Intermediate/Advanced Research Design and Statistics
NASA Technical Reports Server (NTRS)
Ploutz-Snyder, Robert
2009-01-01
The purpose of this module is To provide Institutional Researchers (IRs) with an understanding of the principles of advanced research design and the intermediate/advanced statistical procedures consistent with such designs
Deconstructing Statistical Analysis
ERIC Educational Resources Information Center
Snell, Joel
2014-01-01
Using a very complex statistical analysis and research method for the sake of enhancing the prestige of an article or making a new product or service legitimate needs to be monitored and questioned for accuracy. 1) The more complicated the statistical analysis, and research the fewer the number of learned readers can understand it. This adds a…
Statistical Analysis of RTS Noise and Low Frequency Noise in 1M MOSFETs Using an Advanced TEG
NASA Astrophysics Data System (ADS)
Abe, K.; Sugawa, S.; Watabe, S.; Miyamoto, N.; Teramoto, A.; Toita, M.; Kamata, Y.; Shibusawa, K.; Ohmi, T.
2007-07-01
In this paper, we developed an advanced Test Element Group (TEG) which can measure Random Telegraph Signal (RTS) noise in over 106 nMOSFETs including various gate sizes with high accuracy in a very short time. We measured and analyzed these noises statistically, as the result, we confirmed that appearance probabilities in the TEG and noise intensities of RTS are dependent on gate sizes.
Writing to Learn Statistics in an Advanced Placement Statistics Course
ERIC Educational Resources Information Center
Northrup, Christian Glenn
2012-01-01
This study investigated the use of writing in a statistics classroom to learn if writing provided a rich description of problem-solving processes of students as they solved problems. Through analysis of 329 written samples provided by students, it was determined that writing provided a rich description of problem-solving processes and enabled…
Advance Report of Final Mortality Statistics, 1985.
ERIC Educational Resources Information Center
Monthly Vital Statistics Report, 1987
1987-01-01
This document presents mortality statistics for 1985 for the entire United States. Data analysis and discussion of these factors is included: death and death rates; death rates by age, sex, and race; expectation of life at birth and at specified ages; causes of death; infant mortality; and maternal mortality. Highlights reported include: (1) the…
Advances in Statistical Methods for Substance Abuse Prevention Research
MacKinnon, David P.; Lockwood, Chondra M.
2010-01-01
The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods. PMID:12940467
Statistical log analysis made practical
Mitchell, W.K.; Nelson, R.J. )
1991-06-01
This paper discusses the advantages of a statistical approach to log analysis. Statistical techniques use inverse methods to calculate formation parameters. The use of statistical techniques has been limited, however, by the complexity of the mathematics and lengthy computer time required to minimize traditionally used nonlinear equations.
Sikirzhytski, Vitali; Sikirzhytskaya, Aliaksandra; Lednev, Igor K
2012-10-10
Conventional confirmatory biochemical tests used in the forensic analysis of body fluid traces found at a crime scene are destructive and not universal. Recently, we reported on the application of near-infrared (NIR) Raman microspectroscopy for non-destructive confirmatory identification of pure blood, saliva, semen, vaginal fluid and sweat. Here we expand the method to include dry mixtures of semen and blood. A classification algorithm was developed for differentiating pure body fluids and their mixtures. The classification methodology is based on an effective combination of Support Vector Machine (SVM) regression (data selection) and SVM Discriminant Analysis of preprocessed experimental Raman spectra collected using an automatic mapping of the sample. This extensive cross-validation of the obtained results demonstrated that the detection limit of the minor contributor is as low as a few percent. The developed methodology can be further expanded to any binary mixture of complex solutions, including but not limited to mixtures of other body fluids.
Hahn, A.A.
1994-11-01
The complexity of instrumentation sometimes requires data analysis to be done before the result is presented to the control room. This tutorial reviews some of the theoretical assumptions underlying the more popular forms of data analysis and presents simple examples to illuminate the advantages and hazards of different techniques.
Conceptualizing a Framework for Advanced Placement Statistics Teaching Knowledge
ERIC Educational Resources Information Center
Haines, Brenna
2015-01-01
The purpose of this article is to sketch a conceptualization of a framework for Advanced Placement (AP) Statistics Teaching Knowledge. Recent research continues to problematize the lack of knowledge and preparation among secondary level statistics teachers. The College Board's AP Statistics course continues to grow and gain popularity, but is a…
Enhanced bio-manufacturing through advanced multivariate statistical technologies.
Martin, E B; Morris, A J
2002-11-13
The paper describes the interrogation of data, from a reaction vessel producing an active pharmaceutical ingredient (API), using advanced multivariate statistical techniques. Due to the limited number of batches available, data augmentation was used to increase the number of batches thereby enabling the extraction of more subtle process behaviour from the data. A second methodology investigated was that of multi-group modelling. This allowed between cluster variability to be removed, thus allowing attention to focus on within process variability. The paper describes how the different approaches enabled the realisation of a better understanding of the factors causing the onset of an impurity formation to be obtained as well demonstrating the power of multivariate statistical data analysis techniques to provide an enhanced understanding of the process.
A Hierarchical Statistic Methodology for Advanced Memory System Evaluation
Sun, X.-J.; He, D.; Cameron, K.W.; Luo, Y.
1999-04-12
Advances in technology have resulted in a widening of the gap between computing speed and memory access time. Data access time has become increasingly important for computer system design. Various hierarchical memory architectures have been developed. The performance of these advanced memory systems, however, varies with applications and problem sizes. How to reach an optimal cost/performance design eludes researchers still. In this study, the authors introduce an evaluation methodology for advanced memory systems. This methodology is based on statistical factorial analysis and performance scalability analysis. It is two fold: it first determines the impact of memory systems and application programs toward overall performance; it also identifies the bottleneck in a memory hierarchy and provides cost/performance comparisons via scalability analysis. Different memory systems can be compared in terms of mean performance or scalability over a range of codes and problem sizes. Experimental testing has been performed extensively on the Department of Energy's Accelerated Strategic Computing Initiative (ASCI) machines and benchmarks available at the Los Alamos National Laboratory to validate this newly proposed methodology. Experimental and analytical results show this methodology is simple and effective. It is a practical tool for memory system evaluation and design. Its extension to general architectural evaluation and parallel computer systems are possible and should be further explored.
Advanced Algorithms and Statistics for MOS Surveys
NASA Astrophysics Data System (ADS)
Bolton, A. S.
2016-10-01
This paper presents an individual view on the current state of computational data processing and statistics for inference and discovery in multi-object spectroscopic surveys, supplemented by a historical perspective and a few present-day applications. It is more op-ed than review, and hopefully more readable as a result.
ERIC Educational Resources Information Center
Osler, James Edward, II
2015-01-01
This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…
Tools for Basic Statistical Analysis
NASA Technical Reports Server (NTRS)
Luz, Paul L.
2005-01-01
Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.
Statistical Analysis of RNA Backbone
Hershkovitz, Eli; Sapiro, Guillermo; Tannenbaum, Allen; Williams, Loren Dean
2009-01-01
Local conformation is an important determinant of RNA catalysis and binding. The analysis of RNA conformation is particularly difficult due to the large number of degrees of freedom (torsion angles) per residue. Proteins, by comparison, have many fewer degrees of freedom per residue. In this work, we use and extend classical tools from statistics and signal processing to search for clusters in RNA conformational space. Results are reported both for scalar analysis, where each torsion angle is separately studied, and for vectorial analysis, where several angles are simultaneously clustered. Adapting techniques from vector quantization and clustering to the RNA structure, we find torsion angle clusters and RNA conformational motifs. We validate the technique using well-known conformational motifs, showing that the simultaneous study of the total torsion angle space leads to results consistent with known motifs reported in the literature and also to the finding of new ones. PMID:17048391
NASA Astrophysics Data System (ADS)
Balasis, G.; Papadimitriou, C.; Daglis, I. A.; Georgiou, M.; Giamini, S. A.
2013-12-01
In the past decade, a critical mass of high-quality scientific data on the electric and magnetic fields in the Earth's magnetosphere and topside ionosphere has been progressively collected. This data pool will be further enriched by the measurements of the upcoming ESA/Swarm mission, a constellation of three satellites in three different polar orbits between 400 and 550 km altitude, which is expected to be launched in November 2013. New analysis tools that can cope with measurements of various spacecraft at various regions of the magnetosphere and in the topside ionosphere as well as ground stations will effectively enhance the scientific exploitation of the accumulated data. Here, we report on a new suite of algorithms based on a combination of wavelet spectral methods and artificial neural network techniques and demonstrate the applicability of our recently developed analysis tools both for individual case studies and statistical studies of ultra-low frequency (ULF) waves. First, we provide evidence for a rare simultaneous observation of a ULF wave event in the Earth's magnetosphere, topside ionosphere and surface: we have found a specific time interval during the Halloween 2003 magnetic storm, when the Cluster and CHAMP spacecraft were in good local time (LT) conjunction, and have examined the ULF wave activity in the Pc3 (22-100 mHz) and Pc4-5 (1-22 mHz) bands using data from the Geotail, Cluster and CHAMP missions, as well as the CARISMA and GIMA magnetometer networks. Then, we perform a statistical study of Pc3 wave events observed by CHAMP for the full decade (2001-2010) of the satellite vector magnetic data: the creation of a database of such events enabled us to derive valuable statistics for many important physical properties relating to the spatio-temporal location of these waves, the wave power and frequency, as well as other parameters and their correlation with solar wind conditions, magnetospheric indices, electron density data, ring current decay
Statistical Analysis of Tsunami Variability
NASA Astrophysics Data System (ADS)
Zolezzi, Francesca; Del Giudice, Tania; Traverso, Chiara; Valfrè, Giulio; Poggi, Pamela; Parker, Eric J.
2010-05-01
similar to that seen in ground motion attenuation correlations used for seismic hazard assessment. The second issue was intra-event variability. This refers to the differences in tsunami wave run-up along a section of coast during a single event. Intra-event variability investigated directly considering field observations. The tsunami events used in the statistical evaluation were selected on the basis of the completeness and reliability of the available data. Tsunami considered for the analysis included the recent and well surveyed tsunami of Boxing Day 2004 (Great Indian Ocean Tsunami), Java 2006, Okushiri 1993, Kocaeli 1999, Messina 1908 and a case study of several historic events in Hawaii. Basic statistical analysis was performed on the field observations from these tsunamis. For events with very wide survey regions, the run-up heights have been grouped in order to maintain a homogeneous distance from the source. Where more than one survey was available for a given event, the original datasets were maintained separately to avoid combination of non-homogeneous data. The observed run-up measurements were used to evaluate the minimum, maximum, average, standard deviation and coefficient of variation for each data set. The minimum coefficient of variation was 0.12 measured for the 2004 Boxing Day tsunami at Nias Island (7 data) while the maximum is 0.98 for the Okushiri 1993 event (93 data). The average coefficient of variation is of the order of 0.45.
Remus, Jeremiah J.; Gottfried, Jennifer L.; Harmon, Russell S.; Draucker, Anne; Baron, Dirk; Yohe, Robert
2010-05-01
of the classifier setup considered in this study include the training/testing routine (a 27-fold leave-one-sample-out setup versus a simple split of the data into separate sets for training and evaluation), the number of latent variables used in the regression model, and whether PLSDA operating on the entire broadband LIBS spectrum is superior to that using only a selected subset of LIBS emission lines. The results point to the robustness of the PLSDA technique and suggest that LIBS analysis combined with the appropriate statistical signal processing has the potential to be a useful tool for chemical analysis of archaeological artifacts and geological specimens.
Tools for the advancement of undergraduate statistics education
NASA Astrophysics Data System (ADS)
Schaffner, Andrew Alan
To keep pace with advances in applied statistics and to maintain literate consumers of quantitative analyses, statistics educators stress the need for change in the classroom (Cobb, 1992; Garfield, 1993, 1995; Moore, 1991a; Snee, 1993; Steinhorst and Keeler, 1995). These authors stress a more concept oriented undergraduate introductory statistics course which emphasizes true understanding over mechanical skills. Drawing on recent educational research, this dissertation attempts to realize this vision by developing tools and pedagogy to assist statistics instructors. This dissertation describes statistical facets, pieces of statistical understanding that are building blocks of knowledge, and discusses DIANA, a World-Wide Web tool for diagnosing facets. Further, I show how facets may be incorporated into course design through the development of benchmark lessons based on the principles of collaborative learning (diSessa and Minstrell, 1995; Cohen, 1994; Reynolds et al., 1995; Bruer, 1993; von Glasersfeld, 1991) and activity based courses (Jones, 1991; Yackel, Cobb and Wood, 1991). To support benchmark lessons and collaborative learning in large classes I describe Virtual Benchmark Instruction, benchmark lessons which take place on a structured hypertext bulletin board using the technology of the World-Wide Web. Finally, I present randomized experiments which suggest that these educational developments are effective in a university introductory statistics course.
Project T.E.A.M. (Technical Education Advancement Modules). Advanced Statistical Process Control.
ERIC Educational Resources Information Center
Dunlap, Dale
This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 20-hour advanced statistical process control (SPC) and quality improvement course designed to develop the following competencies: (1) understanding quality systems; (2) knowing the process; (3) solving quality problems; and (4)…
Asymptotic modal analysis and statistical energy analysis
NASA Technical Reports Server (NTRS)
Dowell, Earl H.
1992-01-01
Asymptotic Modal Analysis (AMA) is a method which is used to model linear dynamical systems with many participating modes. The AMA method was originally developed to show the relationship between statistical energy analysis (SEA) and classical modal analysis (CMA). In the limit of a large number of modes of a vibrating system, the classical modal analysis result can be shown to be equivalent to the statistical energy analysis result. As the CMA result evolves into the SEA result, a number of systematic assumptions are made. Most of these assumptions are based upon the supposition that the number of modes approaches infinity. It is for this reason that the term 'asymptotic' is used. AMA is the asymptotic result of taking the limit of CMA as the number of modes approaches infinity. AMA refers to any of the intermediate results between CMA and SEA, as well as the SEA result which is derived from CMA. The main advantage of the AMA method is that individual modal characteristics are not required in the model or computations. By contrast, CMA requires that each modal parameter be evaluated at each frequency. In the latter, contributions from each mode are computed and the final answer is obtained by summing over all the modes in the particular band of interest. AMA evaluates modal parameters only at their center frequency and does not sum the individual contributions from each mode in order to obtain a final result. The method is similar to SEA in this respect. However, SEA is only capable of obtaining spatial averages or means, as it is a statistical method. Since AMA is systematically derived from CMA, it can obtain local spatial information as well.
Advanced PFBC transient analysis
White, J.S.; Bonk, D.L.
1997-05-01
Transient modeling and analysis of advanced Pressurized Fluidized Bed Combustion (PFBC) systems is a research area that is currently under investigation by the US Department of Energy`s Federal Energy Technology Center (FETC). The object of the effort is to identify key operating parameters that affect plant performance and then quantify the basic response of major sub-systems to changes in operating conditions. PC-TRAX{trademark}, a commercially available dynamic software program, was chosen and applied in this modeling and analysis effort. This paper describes the development of a series of TRAX-based transient models of advanced PFBC power plants. These power plants burn coal or other suitable fuel in a PFBC, and the high temperature flue gas supports low-Btu fuel gas or natural gas combustion in a gas turbine topping combustor. When it is utilized, the low-Btu fuel gas is produced in a bubbling bed carbonizer. High temperature, high pressure combustion products exiting the topping combustor are expanded in a modified gas turbine to generate electrical power. Waste heat from the system is used to raise and superheat steam for a reheat steam turbine bottoming cycle that generates additional electrical power. Basic control/instrumentation models were developed and modeled in PC-TRAX and used to investigate off-design plant performance. System performance for various transient conditions and control philosophies was studied.
Statistical analysis of planetary surfaces
NASA Astrophysics Data System (ADS)
Schmidt, Frederic; Landais, Francois; Lovejoy, Shaun
2015-04-01
In the last decades, a huge amount of topographic data has been obtained by several techniques (laser and radar altimetry, DTM…) for different bodies in the solar system, including Earth, Mars, the Moon etc.. In each case, topographic fields exhibit an extremely high variability with details at each scale, from millimeter to thousands of kilometers. This complexity seems to prohibit global descriptions or global topography models. Nevertheless, this topographic complexity is well-known to exhibit scaling laws that establish a similarity between scales and permit simpler descriptions and models. Indeed, efficient simulations can be made using the statistical properties of scaling fields (fractals). But realistic simulations of global topographic fields must be multi (not mono) scaling behaviour, reflecting the extreme variability and intermittency observed in real fields that can not be generated by simple scaling models. A multiscaling theory has been developed in order to model high variability and intermittency. This theory is a good statistical candidate to model the topography field with a limited number of parameters (called the multifractal parameters). In our study, we show that statistical properties of the Martian topography is accurately reproduced by this model, leading to new interpretation of geomorphological processes.
Statistical Power in Meta-Analysis
ERIC Educational Resources Information Center
Liu, Jin
2015-01-01
Statistical power is important in a meta-analysis study, although few studies have examined the performance of simulated power in meta-analysis. The purpose of this study is to inform researchers about statistical power estimation on two sample mean difference test under different situations: (1) the discrepancy between the analytical power and…
Multivariate statistical analysis of wildfires in Portugal
NASA Astrophysics Data System (ADS)
Costa, Ricardo; Caramelo, Liliana; Pereira, Mário
2013-04-01
Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).
Asymptotic modal analysis and statistical energy analysis
NASA Technical Reports Server (NTRS)
Dowell, Earl H.
1988-01-01
Statistical Energy Analysis (SEA) is defined by considering the asymptotic limit of Classical Modal Analysis, an approach called Asymptotic Modal Analysis (AMA). The general approach is described for both structural and acoustical systems. The theoretical foundation is presented for structural systems, and experimental verification is presented for a structural plate responding to a random force. Work accomplished subsequent to the grant initiation focusses on the acoustic response of an interior cavity (i.e., an aircraft or spacecraft fuselage) with a portion of the wall vibrating in a large number of structural modes. First results were presented at the ASME Winter Annual Meeting in December, 1987, and accepted for publication in the Journal of Vibration, Acoustics, Stress and Reliability in Design. It is shown that asymptotically as the number of acoustic modes excited becomes large, the pressure level in the cavity becomes uniform except at the cavity boundaries. However, the mean square pressure at the cavity corner, edge and wall is, respectively, 8, 4, and 2 times the value in the cavity interior. Also it is shown that when the portion of the wall which is vibrating is near a cavity corner or edge, the response is significantly higher.
Collecting operational event data for statistical analysis
Atwood, C.L.
1994-09-01
This report gives guidance for collecting operational data to be used for statistical analysis, especially analysis of event counts. It discusses how to define the purpose of the study, the unit (system, component, etc.) to be studied, events to be counted, and demand or exposure time. Examples are given of classification systems for events in the data sources. A checklist summarizes the essential steps in data collection for statistical analysis.
Statistical Survey and Analysis Handbook.
ERIC Educational Resources Information Center
Smith, Kenneth F.
The National Food and Agriculture Council of the Philippines regularly requires rapid feedback data for analysis, which will assist in monitoring programs to improve and increase the production of selected crops by small scale farmers. Since many other development programs in various subject matter areas also require similar statistical…
Advanced statistical methods for the definition of new staging models.
Kates, Ronald; Schmitt, Manfred; Harbeck, Nadia
2003-01-01
Adequate staging procedures are the prerequisite for individualized therapy concepts in cancer, particularly in the adjuvant setting. Molecular staging markers tend to characterize specific, fundamental disease processes to a greater extent than conventional staging markers. At the biological level, the course of the disease will almost certainly involve interactions between multiple underlying processes. Since new therapeutic strategies tend to target specific processes as well, their impact will also involve interactions. Hence, assessment of the prognostic impact of new markers and their utilization for prediction of response to therapy will require increasingly sophisticated statistical tools that are capable of detecting and modeling complicated interactions. Because they are designed to model arbitrary interactions, neural networks offer a promising approach to improved staging. However, the typical clinical data environment poses severe challenges to high-performance survival modeling using neural nets, particularly the key problem of maintaining good generalization. Nonetheless, it turns out that by using newly developed methods to minimize unnecessary complexity in the neural network representation of disease course, it is possible to obtain models with high predictive performance. This performance has been validated on both simulated and real patient data sets. There are important applications for design of studies involving targeted therapy concepts and for identification of the improvement in decision support resulting from new staging markers. In this article, advantages of advanced statistical methods such as neural networks for definition of new staging models will be illustrated using breast cancer as an example.
Statistical Analysis For Nucleus/Nucleus Collisions
NASA Technical Reports Server (NTRS)
Mcguire, Stephen C.
1989-01-01
Report describes use of several statistical techniques to charactertize angular distributions of secondary particles emitted in collisions of atomic nuclei in energy range of 24 to 61 GeV per nucleon. Purpose of statistical analysis to determine correlations between intensities of emitted particles and angles comfirming existence of quark/gluon plasma.
Explorations in Statistics: The Analysis of Change
ERIC Educational Resources Information Center
Curran-Everett, Douglas; Williams, Calvin L.
2015-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of "Explorations in Statistics" explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can…
Statistical Analysis of Nondisjunction Assays in Drosophila
Zeng, Yong; Li, Hua; Schweppe, Nicole M.; Hawley, R. Scott; Gilliland, William D.
2010-01-01
Many advances in the understanding of meiosis have been made by measuring how often errors in chromosome segregation occur. This process of nondisjunction can be studied by counting experimental progeny, but direct measurement of nondisjunction rates is complicated by not all classes of nondisjunctional progeny being viable. For X chromosome nondisjunction in Drosophila female meiosis, all of the normal progeny survive, while nondisjunctional eggs produce viable progeny only if fertilized by sperm that carry the appropriate sex chromosome. The rate of nondisjunction has traditionally been estimated by assuming a binomial process and doubling the number of observed nondisjunctional progeny, to account for the inviable classes. However, the correct way to derive statistics (such as confidence intervals or hypothesis testing) by this approach is far from clear. Instead, we use the multinomial-Poisson hierarchy model and demonstrate that the old estimator is in fact the maximum-likelihood estimator (MLE). Under more general assumptions, we derive asymptotic normality of this estimator and construct confidence interval and hypothesis testing formulae. Confidence intervals under this framework are always larger than under the binomial framework, and application to published data shows that use of the multinomial approach can avoid an apparent type 1 error made by use of the binomial assumption. The current study provides guidance for researchers designing genetic experiments on nondisjunction and improves several methods for the analysis of genetic data. PMID:20660647
A Statistical Analysis of Cotton Fiber Properties
NASA Astrophysics Data System (ADS)
Ghosh, Anindya; Das, Subhasis; Majumder, Asha
2016-04-01
This paper reports a statistical analysis of different cotton fiber properties, such as strength, breaking elongation, upper half mean length, length uniformity index, short fiber index, micronaire, reflectance and yellowness measured from 1200 cotton bales. The uni-variate, bi-variate and multi-variate statistical analysis have been invoked to elicit interrelationship between above-mentioned properties taking them up singularly, pairwise and multiple way, respectively. In multi-variate analysis all cotton fiber properties are simultaneously considered for multi-dimensional techniques of principal factor analysis.
ERIC Educational Resources Information Center
Osler, James Edward; Waden, Carl
2013-01-01
This paper discusses the implementation of the Tri-Squared Test as one of many advanced statistical measures used to verify and validate the outcomes of an initial study on academic professional's perspectives on the use, success, and viability of 9th Grade Freshman Academies, Centers, and Center Models. The initial research investigation…
Statistics analysis embedded in spatial DBMS
NASA Astrophysics Data System (ADS)
Chen, Rongguo; Chen, Siqing
2006-10-01
This article sets forth the principle and methodology for implementing spatial database management system (DBMS) by using open source object-relational DBMS - PostgreSQL. The geospatial data model and spatial analysis and processing operations for spatial objects and datasets can be inserted into the DBMS by extended SQL. To implement the statistics analysis embedded in spatial DBMS, an open source statistical program R is introduced to extend the capability of the spatial DBMS. R is a language and environment for statistical computing and graphics. There is a large sum of statistical methods in the form of packages in R. Many classical and modern spatial statistical techniques are implemented in R environment. PL/R is a loadable procedural language containing most of the capabilities in R language which is extensible and enables user to write DBMS functions and triggers in R language. Therefore, the PL/R will extend its capability of spatial statistics and geostatistics when the two kinds of packages are loaded into R language. The PL/R can be extended without limit so that any new method of statistics analysis embedded into the spatial DBMS becomes very convenient.
Statistical Analysis Techniques for Small Sample Sizes
NASA Technical Reports Server (NTRS)
Navard, S. E.
1984-01-01
The small sample sizes problem which is encountered when dealing with analysis of space-flight data is examined. Because of such a amount of data available, careful analyses are essential to extract the maximum amount of information with acceptable accuracy. Statistical analysis of small samples is described. The background material necessary for understanding statistical hypothesis testing is outlined and the various tests which can be done on small samples are explained. Emphasis is on the underlying assumptions of each test and on considerations needed to choose the most appropriate test for a given type of analysis.
Statistical Tools for Forensic Analysis of Toolmarks
David Baldwin; Max Morris; Stan Bajic; Zhigang Zhou; James Kreiser
2004-04-22
Recovery and comparison of toolmarks, footprint impressions, and fractured surfaces connected to a crime scene are of great importance in forensic science. The purpose of this project is to provide statistical tools for the validation of the proposition that particular manufacturing processes produce marks on the work-product (or tool) that are substantially different from tool to tool. The approach to validation involves the collection of digital images of toolmarks produced by various tool manufacturing methods on produced work-products and the development of statistical methods for data reduction and analysis of the images. The developed statistical methods provide a means to objectively calculate a ''degree of association'' between matches of similarly produced toolmarks. The basis for statistical method development relies on ''discriminating criteria'' that examiners use to identify features and spatial relationships in their analysis of forensic samples. The developed data reduction algorithms utilize the same rules used by examiners for classification and association of toolmarks.
Investigation of Weibull statistics in fracture analysis of cast aluminum
NASA Technical Reports Server (NTRS)
Holland, Frederic A., Jr.; Zaretsky, Erwin V.
1989-01-01
The fracture strengths of two large batches of A357-T6 cast aluminum coupon specimens were compared by using two-parameter Weibull analysis. The minimum number of these specimens necessary to find the fracture strength of the material was determined. The applicability of three-parameter Weibull analysis was also investigated. A design methodology based on the combination of elementary stress analysis and Weibull statistical analysis is advanced and applied to the design of a spherical pressure vessel shell. The results from this design methodology are compared with results from the applicable ASME pressure vessel code.
Han, Yali; Liu, Jie; Sun, Meili; Zhang, Zongpu; Liu, Chuanyong; Sun, Yuping
2016-01-01
Background. There is no definitive conclusion so far on the predictive values of ERCC1 polymorphisms for clinical outcomes of platinum-based chemotherapy in non-small cell lung cancer (NSCLC). We updated this meta-analysis with an expectation to obtain some statistical advancement on this issue. Methods. Relevant studies were identified by searching MEDLINE, EMBASE databases from inception to April 2015. Primary outcomes included objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). All analyses were performed using the Review Manager version 5.3 and the Stata version 12.0. Results. A total of 33 studies including 5373 patients were identified. ERCC1 C118T and C8092A could predict both ORR and OS for platinum-based chemotherapy in Asian NSCLC patients (CT + TT versus CC, ORR: OR = 0.80, 95% CI = 0.67–0.94; OS: HR = 1.24, 95% CI = 1.01–1.53) (CA + AA versus CC, ORR: OR = 0.76, 95% CI = 0.60–0.96; OS: HR = 1.37, 95% CI = 1.06–1.75). Conclusions. Current evidence strongly indicated the prospect of ERCC1 C118T and C8092A as predictive biomarkers for platinum-based chemotherapy in Asian NSCLC patients. However, the results should be interpreted with caution and large prospective studies are still required to further investigate these findings. PMID:27057082
Statistical Analysis Experiment for Freshman Chemistry Lab.
ERIC Educational Resources Information Center
Salzsieder, John C.
1995-01-01
Describes a laboratory experiment dissolving zinc from galvanized nails in which data can be gathered very quickly for statistical analysis. The data have sufficient significant figures and the experiment yields a nice distribution of random errors. Freshman students can gain an appreciation of the relationships between random error, number of…
MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS
Microarray Data Analysis Using Multiple Statistical Models
Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...
Applied Behavior Analysis and Statistical Process Control?
ERIC Educational Resources Information Center
Hopkins, B. L.
1995-01-01
Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…
Statistical shape analysis: From landmarks to diffeomorphisms.
Zhang, Miaomiao; Golland, Polina
2016-10-01
We offer a blazingly brief review of evolution of shape analysis methods in medical imaging. As the representations and the statistical models grew more sophisticated, the problem of shape analysis has been gradually redefined to accept images rather than binary segmentations as a starting point. This transformation enabled shape analysis to take its rightful place in the arsenal of tools for extracting and understanding patterns in large clinical image sets. We speculate on the future developments in shape analysis and potential applications that would bring this mathematically rich area to bear on clinical practice. PMID:27377332
Advances in Testing the Statistical Significance of Mediation Effects
ERIC Educational Resources Information Center
Mallinckrodt, Brent; Abraham, W. Todd; Wei, Meifen; Russell, Daniel W.
2006-01-01
P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…
Statistical Analysis of Big Data on Pharmacogenomics
Fan, Jianqing; Liu, Han
2013-01-01
This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905
Statistical Analysis of Thermal Analysis Margin
NASA Technical Reports Server (NTRS)
Garrison, Matthew B.
2011-01-01
NASA Goddard Space Flight Center requires that each project demonstrate a minimum of 5 C margin between temperature predictions and hot and cold flight operational limits. The bounding temperature predictions include worst-case environment and thermal optical properties. The purpose of this work is to: assess how current missions are performing against their pre-launch bounding temperature predictions and suggest any possible changes to the thermal analysis margin rules
NASA Technical Reports Server (NTRS)
Greenberg, Marc W.; Laing, William
2013-01-01
An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.
Comparative statistical analysis of planetary surfaces
NASA Astrophysics Data System (ADS)
Schmidt, Frédéric; Landais, Francois; Lovejoy, Shaun
2016-04-01
In the present study, we aim to provide a statistical and comparative description of topographic fields by using the huge amount of topographic data available for different bodies in the solar system, including Earth, Mars, the Moon etc.. Our goal is to characterize and quantify the geophysical processes involved by a relevant statistical description. In each case, topographic fields exhibit an extremely high variability with details at each scale, from millimeter to thousands of kilometers. This complexity seems to prohibit global descriptions or global topography models. Nevertheless, this topographic complexity is well-known to exhibit scaling laws that establish a similarity between scales and permit simpler descriptions and models. Indeed, efficient simulations can be made using the statistical properties of scaling fields (fractals). But realistic simulations of global topographic fields must be multi (not mono) scaling behaviour, reflecting the extreme variability and intermittency observed in real fields that can not be generated by simple scaling models. A multiscaling theory has been developed in order to model high variability and intermittency. This theory is a good statistical candidate to model the topography field with a limited number of parameters (called the multifractal parameters). After a global analysis of Mars (Landais et. al, 2015) we have performed similar analysis on different body in the solar system including the Moon, Venus and mercury indicating that the mulifractal parameters might be relevant to explain the competition between several processes operating on multiple scales
Statistical Analysis of Iberian Peninsula Megaliths Orientations
NASA Astrophysics Data System (ADS)
González-García, A. C.
2009-08-01
Megalithic monuments have been intensively surveyed and studied from the archaeoastronomical point of view in the past decades. We have orientation measurements for over one thousand megalithic burial monuments in the Iberian Peninsula, from several different periods. These data, however, lack a sound understanding. A way to classify and start to understand such orientations is by means of statistical analysis of the data. A first attempt is done with simple statistical variables and a mere comparison between the different areas. In order to minimise the subjectivity in the process a further more complicated analysis is performed. Some interesting results linking the orientation and the geographical location will be presented. Finally I will present some models comparing the orientation of the megaliths in the Iberian Peninsula with the rising of the sun and the moon at several times of the year.
Protein Sectors: Statistical Coupling Analysis versus Conservation
Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas
2015-01-01
Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535
Applied behavior analysis and statistical process control?
Hopkins, B L
1995-01-01
This paper examines Pfadt and Wheeler's (1995) suggestions that the methods of statistical process control (SPC) be incorporated into applied behavior analysis. The research strategies of SPC are examined and compared to those of applied behavior analysis. I argue that the statistical methods that are a part of SPC would likely reduce applied behavior analysts' intimate contacts with the problems with which they deal and would, therefore, likely yield poor treatment and research decisions. Examples of these kinds of results and decisions are drawn from the cases and data Pfadt and Wheeler present. This paper also describes and clarifies many common misconceptions about SPC, including W. Edwards Deming's involvement in its development, its relationship to total quality management, and its confusion with various other methods designed to detect sources of unwanted variability. PMID:7592156
Source apportionment advances using polar plots of bivariate correlation and regression statistics
NASA Astrophysics Data System (ADS)
Grange, Stuart K.; Lewis, Alastair C.; Carslaw, David C.
2016-11-01
This paper outlines the development of enhanced bivariate polar plots that allow the concentrations of two pollutants to be compared using pair-wise statistics for exploring the sources of atmospheric pollutants. The new method combines bivariate polar plots, which provide source characteristic information, with pair-wise statistics that provide information on how two pollutants are related to one another. The pair-wise statistics implemented include weighted Pearson correlation and slope from two linear regression methods. The development uses a Gaussian kernel to locally weight the statistical calculations on a wind speed-direction surface together with variable-scaling. Example applications of the enhanced polar plots are presented by using routine air quality data for two monitoring sites in London, United Kingdom for a single year (2013). The London examples demonstrate that the combination of bivariate polar plots, correlation, and regression techniques can offer considerable insight into air pollution source characteristics, which would be missed if only scatter plots and mean polar plots were used for analysis. Specifically, using correlation and slopes as pair-wise statistics, long-range transport processes were isolated and black carbon (BC) contributions to PM2.5 for a kerbside monitoring location were quantified. Wider applications and future advancements are also discussed.
NASA Astrophysics Data System (ADS)
Mountcastle, Donald B.; Bucy, Brandon R.; Thompson, John R.
2007-11-01
Equilibrium properties of macroscopic systems are highly predictable as n, the number of particles approaches and exceeds Avogadro's number; theories of statistical physics depend on these results. Typical pedagogical devices used in statistical physics textbooks to introduce entropy (S) and multiplicity (ω) (where S = k ln(ω)) include flipping coins and/or other equivalent binary events, repeated n times. Prior to instruction, our statistical mechanics students usually gave reasonable answers about the probabilities, but not the relative uncertainties, of the predicted outcomes of such events. However, they reliably predicted that the uncertainty in a measured continuous quantity (e.g., the amount of rainfall) does decrease as the number of measurements increases. Typical textbook presentations assume that students understand that the relative uncertainty of binary outcomes will similarly decrease as the number of events increases. This is at odds with our findings, even though most of our students had previously completed mathematics courses in statistics, as well as an advanced electronics laboratory course that included statistical analysis of distributions of dart scores as n increased.
Multivariate analysis: A statistical approach for computations
NASA Astrophysics Data System (ADS)
Michu, Sachin; Kaushik, Vandana
2014-10-01
Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.
Statistical quality control through overall vibration analysis
NASA Astrophysics Data System (ADS)
Carnero, M. ^{a.} Carmen; González-Palma, Rafael; Almorza, David; Mayorga, Pedro; López-Escobar, Carlos
2010-05-01
The present study introduces the concept of statistical quality control in automotive wheel bearings manufacturing processes. Defects on products under analysis can have a direct influence on passengers' safety and comfort. At present, the use of vibration analysis on machine tools for quality control purposes is not very extensive in manufacturing facilities. Noise and vibration are common quality problems in bearings. These failure modes likely occur under certain operating conditions and do not require high vibration amplitudes but relate to certain vibration frequencies. The vibration frequencies are affected by the type of surface problems (chattering) of ball races that are generated through grinding processes. The purpose of this paper is to identify grinding process variables that affect the quality of bearings by using statistical principles in the field of machine tools. In addition, an evaluation of the quality results of the finished parts under different combinations of process variables is assessed. This paper intends to establish the foundations to predict the quality of the products through the analysis of self-induced vibrations during the contact between the grinding wheel and the parts. To achieve this goal, the overall self-induced vibration readings under different combinations of process variables are analysed using statistical tools. The analysis of data and design of experiments follows a classical approach, considering all potential interactions between variables. The analysis of data is conducted through analysis of variance (ANOVA) for data sets that meet normality and homoscedasticity criteria. This paper utilizes different statistical tools to support the conclusions such as chi squared, Shapiro-Wilks, symmetry, Kurtosis, Cochran, Hartlett, and Hartley and Krushal-Wallis. The analysis presented is the starting point to extend the use of predictive techniques (vibration analysis) for quality control. This paper demonstrates the existence
Analysis and modeling of resistive switching statistics
NASA Astrophysics Data System (ADS)
Long, Shibing; Cagli, Carlo; Ielmini, Daniele; Liu, Ming; Suñé, Jordi
2012-04-01
The resistive random access memory (RRAM), based on the reversible switching between different resistance states, is a promising candidate for next-generation nonvolatile memories. One of the most important challenges to foster the practical application of RRAM is the control of the statistical variation of switching parameters to gain low variability and high reliability. In this work, starting from the well-known percolation model of dielectric breakdown (BD), we establish a framework of analysis and modeling of the resistive switching statistics in RRAM devices, which are based on the formation and disconnection of a conducting filament (CF). One key aspect of our proposal is the relation between the CF resistance and the switching statistics. Hence, establishing the correlation between SET and RESET switching variables and the initial resistance of the device in the OFF and ON states, respectively, is a fundamental issue. Our modeling approach to the switching statistics is fully analytical and contains two main elements: (i) a geometrical cell-based description of the CF and (ii) a deterministic model for the switching dynamics. Both ingredients might be slightly different for the SET and RESET processes, for the type of switching (bipolar or unipolar), and for the kind of considered resistive structure (oxide-based, conductive bridge, etc.). However, the basic structure of our approach is thought to be useful for all the cases and should provide a framework for the physics-based understanding of the switching mechanisms and the associated statistics, for the trustful estimation of RRAM performance, and for the successful forecast of reliability. As a first application example, we start by considering the case of the RESET statistics of NiO-based RRAM structures. In particular, we statistically analyze the RESET transitions of a statistically significant number of switching cycles of Pt/NiO/W devices. In the RESET transition, the ON-state resistance (RON) is a
Statistical analysis of diversification with species traits.
Paradis, Emmanuel
2005-01-01
Testing whether some species traits have a significant effect on diversification rates is central in the assessment of macroevolutionary theories. However, we still lack a powerful method to tackle this objective. I present a new method for the statistical analysis of diversification with species traits. The required data are observations of the traits on recent species, the phylogenetic tree of these species, and reconstructions of ancestral values of the traits. Several traits, either continuous or discrete, and in some cases their interactions, can be analyzed simultaneously. The parameters are estimated by the method of maximum likelihood. The statistical significance of the effects in a model can be tested with likelihood ratio tests. A simulation study showed that past random extinction events do not affect the Type I error rate of the tests, whereas statistical power is decreased, though some power is still kept if the effect of the simulated trait on speciation is strong. The use of the method is illustrated by the analysis of published data on primates. The analysis of these data showed that the apparent overall positive relationship between body mass and species diversity is actually an artifact due to a clade-specific effect. Within each clade the effect of body mass on speciation rate was in fact negative. The present method allows to take both effects (clade and body mass) into account simultaneously.
Statistical analysis of Contact Angle Hysteresis
NASA Astrophysics Data System (ADS)
Janardan, Nachiketa; Panchagnula, Mahesh
2015-11-01
We present the results of a new statistical approach to determining Contact Angle Hysteresis (CAH) by studying the nature of the triple line. A statistical distribution of local contact angles on a random three-dimensional drop is used as the basis for this approach. Drops with randomly shaped triple lines but of fixed volumes were deposited on a substrate and their triple line shapes were extracted by imaging. Using a solution developed by Prabhala et al. (Langmuir, 2010), the complete three dimensional shape of the sessile drop was generated. A distribution of the local contact angles for several such drops but of the same liquid-substrate pairs is generated. This distribution is a result of several microscopic advancing and receding processes along the triple line. This distribution is used to yield an approximation of the CAH associated with the substrate. This is then compared with measurements of CAH by means of a liquid infusion-withdrawal experiment. Static measurements are shown to be sufficient to measure quasistatic contact angle hysteresis of a substrate. The approach also points towards the relationship between microscopic triple line contortions and CAH.
Two statistical tests for meiotic breakpoint analysis.
Plaetke, R; Schachtel, G A
1995-01-01
Meiotic breakpoint analysis (BPA), a statistical method for ordering genetic markers, is increasing in importance as a method for building genetic maps of human chromosomes. Although BPA does not provide estimates of genetic distances between markers, it efficiently locates new markers on already defined dense maps, when likelihood analysis becomes cumbersome or the sample size is small. However, until now no assessments of statistical significance have been available for evaluating the possibility that the results of a BPA were produced by chance. In this paper, we propose two statistical tests to determine whether the size of a sample and its genetic information content are sufficient to distinguish between "no linkage" and "linkage" of a marker mapped by BPA to a certain region. Both tests are exact and should be conducted after a BPA has assigned the marker to an interval on the map. Applications of the new tests are demonstrated by three examples: (1) a synthetic data set, (2) a data set of five markers on human chromosome 8p, and (3) a data set of four markers on human chromosome 17q. PMID:7847387
Statistical Considerations for Analysis of Microarray Experiments
Owzar, Kouros; Barry, William T.; Jung, Sin-Ho
2014-01-01
Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generate a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results. PMID:22212230
Statistical Analysis of Zebrafish Locomotor Response.
Liu, Yiwen; Carmer, Robert; Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai
2015-01-01
Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling's T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling's T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure. PMID:26437184
Statistical analysis of extreme auroral electrojet indices
NASA Astrophysics Data System (ADS)
Nakamura, Masao; Yoneda, Asato; Oda, Mitsunobu; Tsubouchi, Ken
2015-09-01
Extreme auroral electrojet activities can damage electrical power grids due to large induced currents in the Earth, degrade radio communications and navigation systems due to the ionospheric disturbances and cause polar-orbiting satellite anomalies due to the enhanced auroral electron precipitation. Statistical estimation of extreme auroral electrojet activities is an important factor in space weather research. For this estimation, we utilize extreme value theory (EVT), which focuses on the statistical behavior in the tail of a distribution. As a measure of auroral electrojet activities, auroral electrojet indices AL, AU, and AE, are used, which describe the maximum current strength of the westward and eastward auroral electrojets and the sum of the two oppositely directed in the auroral latitude ionosphere, respectively. We provide statistical evidence for finite upper limits to AL and AU and estimate the annual expected number and probable intensity of their extreme events. We detect two different types of extreme AE events; therefore, application of the appropriate EVT analysis to AE is difficult.
Statistical Hot Channel Analysis for the NBSR
Cuadra A.; Baek J.
2014-05-27
A statistical analysis of thermal limits has been carried out for the research reactor (NBSR) at the National Institute of Standards and Technology (NIST). The objective of this analysis was to update the uncertainties of the hot channel factors with respect to previous analysis for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuels. Although uncertainties in key parameters which enter into the analysis are not yet known for the LEU core, the current analysis uses reasonable approximations instead of conservative estimates based on HEU values. Cumulative distribution functions (CDFs) were obtained for critical heat flux ratio (CHFR), and onset of flow instability ratio (OFIR). As was done previously, the Sudo-Kaminaga correlation was used for CHF and the Saha-Zuber correlation was used for OFI. Results were obtained for probability levels of 90%, 95%, and 99.9%. As an example of the analysis, the results for both the existing reactor with HEU fuel and the LEU core show that CHFR would have to be above 1.39 to assure with 95% probability that there is no CHF. For the OFIR, the results show that the ratio should be above 1.40 to assure with a 95% probability that OFI is not reached.
Advances in assessing geomorphic plausibility in statistical susceptibility modelling
NASA Astrophysics Data System (ADS)
Steger, Stefan; Brenning, Alexander; Bell, Rainer; Petschko, Helene; Glade, Thomas
2014-05-01
The quality, reliability and applicability of landslide susceptibility maps is regularly deduced directly by interpreting quantitative model performance measures. These quantitative estimates are usually calculated for an independent test sample of a landslide inventory. Numerous studies demonstrate that totally unbiased landslide inventories are rarely available. We assume that such biases are also inherent in the test sample used to quantitatively validate the models. Therefore we suppose that the explanatory power of statistical performance measures is limited by the quality of the inventory used to calculate these statistics. To investigate this assumption, we generated and validated 16 statistical susceptibility models by using two landslide inventories of differing qualities for the Rhenodanubian Flysch zone of Lower Austria (1,354 km²). The ALS-based (Airborne Laser Scan) Inventory (n=6,218) was mapped purposely for susceptibility modelling from a high resolution hillshade and exhibits a high positional accuracy. The less accurate building ground register (BGR; n=681) provided by the Geological Survey of Lower Austria represents reported damaging events and shows a substantially lower completeness. Both inventories exhibit differing systematic biases regarding the land cover. For instance, due to human impact on the visibility of geomorphic structures (e.g. planation), few ALS landslides could be mapped on settlements and pastures (ALS-mapping bias). In contrast, damaging events were frequently reported for settlements and pastures (BGR-report bias). Susceptibility maps were calculated by applying four multivariate classification methods, namely generalized linear model, generalized additive model, random forest and support vector machine separately for both inventories and two sets of explanatory variables (with and without land cover). Quantitative validation was performed by calculating the area under the receiver operating characteristics curve (AUROC
Statistical Methods Handbook for Advanced Gas Reactor Fuel Materials
J. J. Einerson
2005-05-01
Fuel materials such as kernels, coated particles, and compacts are being manufactured for experiments simulating service in the next generation of high temperature gas reactors. These must meet predefined acceptance specifications. Many tests are performed for quality assurance, and many of these correspond to criteria that must be met with specified confidence, based on random samples. This report describes the statistical methods to be used. The properties of the tests are discussed, including the risk of false acceptance, the risk of false rejection, and the assumption of normality. Methods for calculating sample sizes are also described.
Methods of the computer-aided statistical analysis of microcircuits
NASA Astrophysics Data System (ADS)
Beliakov, Iu. N.; Kurmaev, F. A.; Batalov, B. V.
Methods that are currently used for the computer-aided statistical analysis of microcircuits at the design stage are summarized. In particular, attention is given to methods for solving problems in statistical analysis, statistical planning, and factorial model synthesis by means of irregular experimental design. Efficient ways of reducing the computer time required for statistical analysis and numerical methods of microcircuit analysis are proposed. The discussion also covers various aspects of the organization of computer-aided microcircuit modeling and analysis systems.
The statistical multifragmentation model: Origins and recent advances
NASA Astrophysics Data System (ADS)
Donangelo, R.; Souza, S. R.
2016-07-01
We review the Statistical Multifragmentation Model (SMM) which considers a generalization of the liquid-drop model for hot nuclei and allows one to calculate thermodynamic quantities characterizing the nuclear ensemble at the disassembly stage. We show how to determine probabilities of definite partitions of finite nuclei and how to determine, through Monte Carlo calculations, observables such as the caloric curve, multiplicity distributions, heat capacity, among others. Some experimental measurements of the caloric curve confirmed the SMM predictions of over 10 years before, leading to a surge in the interest in the model. However, the experimental determination of the fragmentation temperatures relies on the yields of different isotopic species, which were not correctly calculated in the schematic, liquid-drop picture, employed in the SMM. This led to a series of improvements in the SMM, in particular to the more careful choice of nuclear masses and energy densities, specially for the lighter nuclei. With these improvements the SMM is able to make quantitative determinations of isotope production. We show the application of SMM to the production of exotic nuclei through multifragmentation. These preliminary calculations demonstrate the need for a careful choice of the system size and excitation energy to attain maximum yields.
On intracluster Faraday rotation. II - Statistical analysis
NASA Technical Reports Server (NTRS)
Lawler, J. M.; Dennison, B.
1982-01-01
The comparison of a reliable sample of radio source Faraday rotation measurements seen through rich clusters of galaxies, with sources seen through the outer parts of clusters and therefore having little intracluster Faraday rotation, indicates that the distribution of rotation in the former population is broadened, but only at the 80% level of statistical confidence. Employing a physical model for the intracluster medium in which the square root of magnetic field strength/turbulent cell per gas core radius number ratio equals approximately 0.07 microgauss, a Monte Carlo simulation is able to reproduce the observed broadening. An upper-limit analysis figure of less than 0.20 microgauss for the field strength/turbulent cell ratio, combined with lower limits on field strength imposed by limitations on the Compton-scattered flux, shows that intracluster magnetic fields must be tangled on scales greater than about 20 kpc.
Statistical Analysis of Cardiovascular Data from FAP
NASA Technical Reports Server (NTRS)
Sealey, Meghan
2016-01-01
pressure, etc.) to see which could best predict how long the subjects could tolerate the tilt tests. With this I plan to analyze an artificial gravity study in order to determine the effects of orthostatic intolerance during spaceflight. From these projects, I became efficient in using the statistical software Stata, which I had previously never used before. I learned new statistical methods, such as mixed-effects linear regression, maximum likelihood estimation on longitudinal data, and post model-fitting tests to see if certain parameters contribute significantly to the model, all of which will better my understanding for when I continue studying for my masters' degree. I was also able to demonstrate my knowledge of statistics by helping other students run statistical analyses for their own projects. After completing these projects, the experience and knowledge gained from completing this analysis exemplifies the type of work that I would like to pursue in the future. After completing my masters' degree, I plan to pursue a career in biostatistics, which is exactly the position that I interned as, and I plan to use this experience to contribute to that goal
Analysis of Variance: What Is Your Statistical Software Actually Doing?
ERIC Educational Resources Information Center
Li, Jian; Lomax, Richard G.
2011-01-01
Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…
R: a statistical environment for hydrological analysis
NASA Astrophysics Data System (ADS)
Zambrano-Bigiarini, Mauricio; Bellin, Alberto
2010-05-01
The free software environment for statistical computing and graphics "R" has been developed and it is maintained by statistical programmers, with the support of an increasing community of users with many different backgrounds, which allows access to both well-established and experimental techniques. Hydrological modelling practitioners spent large amount of time in pre- and post-processing data and results with traditional instruments. In this work "R" and some of its packages are presented as powerful tools to explore and extract patterns from raw information, to pre-process input data of hydrological models, and post-processing its results. In particular, examples are taken from analysing 30-years of daily data for a basin of 85000 km2, saving a large amount of time that could be better spent in doing analysis. In doing so, vectorial and raster GIS files were imported, for carrying out spatial and geostatistical analysis. Thousands of raw text files with time series of precipitation, temperature and streamflow were summarized and organized. Gauging stations to be used in the modelling process are selected according to the amount of days with information, and missing time series data are filled in using spatial interpolation. Time series on the gauging stations are summarized through daily, monthly and annual plots. Input files in dbase format are automatically created in a batch process. Results of a hydrological model are compared with observed values through plots and numerical goodness of fit indexes. Two packages specifically developed to assists hydrologists in the previous tasks are briefly presented. At the end, we think the "R" environment would be a valuable tool to support undergraduate and graduate education in hydrology, because it is helpful to capture the main features of large amount of data; it is a flexible and fully functional programming language, able to be interfaced to existing Fortran and C code and well suited to the ever growing demands
An R package for statistical provenance analysis
NASA Astrophysics Data System (ADS)
Vermeesch, Pieter; Resentini, Alberto; Garzanti, Eduardo
2016-05-01
This paper introduces provenance, a software package within the statistical programming environment R, which aims to facilitate the visualisation and interpretation of large amounts of sedimentary provenance data, including mineralogical, petrographic, chemical and isotopic provenance proxies, or any combination of these. provenance comprises functions to: (a) calculate the sample size required to achieve a given detection limit; (b) plot distributional data such as detrital zircon U-Pb age spectra as Cumulative Age Distributions (CADs) or adaptive Kernel Density Estimates (KDEs); (c) plot compositional data as pie charts or ternary diagrams; (d) correct the effects of hydraulic sorting on sandstone petrography and heavy mineral composition; (e) assess the settling equivalence of detrital minerals and grain-size dependence of sediment composition; (f) quantify the dissimilarity between distributional data using the Kolmogorov-Smirnov and Sircombe-Hazelton distances, or between compositional data using the Aitchison and Bray-Curtis distances; (e) interpret multi-sample datasets by means of (classical and nonmetric) Multidimensional Scaling (MDS) and Principal Component Analysis (PCA); and (f) simplify the interpretation of multi-method datasets by means of Generalised Procrustes Analysis (GPA) and 3-way MDS. All these tools can be accessed through an intuitive query-based user interface, which does not require knowledge of the R programming language. provenance is free software released under the GPL-2 licence and will be further expanded based on user feedback.
Sikirzhytskaya, Aliaksandra; Sikirzhytski, Vitali; Lednev, Igor K
2014-01-01
Body fluids are a common and important type of forensic evidence. In particular, the identification of menstrual blood stains is often a key step during the investigation of rape cases. Here, we report on the application of near-infrared Raman microspectroscopy for differentiating menstrual blood from peripheral blood. We observed that the menstrual and peripheral blood samples have similar but distinct Raman spectra. Advanced statistical analysis of the multiple Raman spectra that were automatically (Raman mapping) acquired from the 40 dried blood stains (20 donors for each group) allowed us to build classification model with maximum (100%) sensitivity and specificity. We also demonstrated that despite certain common constituents, menstrual blood can be readily distinguished from vaginal fluid. All of the classification models were verified using cross-validation methods. The proposed method overcomes the problems associated with currently used biochemical methods, which are destructive, time consuming and expensive.
Statistical analysis of regulatory ecotoxicity tests.
Isnard, P; Flammarion, P; Roman, G; Babut, M; Bastien, P; Bintein, S; Esserméant, L; Férard, J F; Gallotti-Schmitt, S; Saouter, E; Saroli, M; Thiébaud, H; Tomassone, R; Vindimian, E
2001-11-01
ANOVA-type data analysis, i.e.. determination of lowest-observed-effect concentrations (LOECs), and no-observed-effect concentrations (NOECs), has been widely used for statistical analysis of chronic ecotoxicity data. However, it is more and more criticised for several reasons, among which the most important is probably the fact that the NOEC depends on the choice of test concentrations and number of replications and rewards poor experiments, i.e., high variability, with high NOEC values. Thus, a recent OECD workshop concluded that the use of the NOEC should be phased out and that a regression-based estimation procedure should be used. Following this workshop, a working group was established at the French level between government, academia and industry representatives. Twenty-seven sets of chronic data (algae, daphnia, fish) were collected and analysed by ANOVA and regression procedures. Several regression models were compared and relations between NOECs and ECx, for different values of x, were established in order to find an alternative summary parameter to the NOEC. Biological arguments are scarce to help in defining a negligible level of effect x for the ECx. With regard to their use in the risk assessment procedures, a convenient methodology would be to choose x so that ECx are on average similar to the present NOEC. This would lead to no major change in the risk assessment procedure. However, experimental data show that the ECx depend on the regression models and that their accuracy decreases in the low effect zone. This disadvantage could probably be reduced by adapting existing experimental protocols but it could mean more experimental effort and higher cost. ECx (derived with existing test guidelines, e.g., regarding the number of replicates) whose lowest bounds of the confidence interval are on average similar to present NOEC would improve this approach by a priori encouraging more precise experiments. However, narrow confidence intervals are not only
Analysis of Advanced Rotorcraft Configurations
NASA Technical Reports Server (NTRS)
Johnson, Wayne
2000-01-01
Advanced rotorcraft configurations are being investigated with the objectives of identifying vehicles that are larger, quieter, and faster than current-generation rotorcraft. A large rotorcraft, carrying perhaps 150 passengers, could do much to alleviate airport capacity limitations, and a quiet rotorcraft is essential for community acceptance of the benefits of VTOL operations. A fast, long-range, long-endurance rotorcraft, notably the tilt-rotor configuration, will improve rotorcraft economics through productivity increases. A major part of the investigation of advanced rotorcraft configurations consists of conducting comprehensive analyses of vehicle behavior for the purpose of assessing vehicle potential and feasibility, as well as to establish the analytical models required to support the vehicle development. The analytical work of FY99 included applications to tilt-rotor aircraft. Tilt Rotor Aeroacoustic Model (TRAM) wind tunnel measurements are being compared with calculations performed by using the comprehensive analysis tool (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD 11)). The objective is to establish the wing and wake aerodynamic models that are required for tilt-rotor analysis and design. The TRAM test in the German-Dutch Wind Tunnel (DNW) produced extensive measurements. This is the first test to encompass air loads, performance, and structural load measurements on tilt rotors, as well as acoustic and flow visualization data. The correlation of measurements and calculations includes helicopter-mode operation (performance, air loads, and blade structural loads), hover (performance and air loads), and airplane-mode operation (performance).
Statistical approach to partial equilibrium analysis
NASA Astrophysics Data System (ADS)
Wang, Yougui; Stanley, H. E.
2009-04-01
A statistical approach to market equilibrium and efficiency analysis is proposed in this paper. One factor that governs the exchange decisions of traders in a market, named willingness price, is highlighted and constitutes the whole theory. The supply and demand functions are formulated as the distributions of corresponding willing exchange over the willingness price. The laws of supply and demand can be derived directly from these distributions. The characteristics of excess demand function are analyzed and the necessary conditions for the existence and uniqueness of equilibrium point of the market are specified. The rationing rates of buyers and sellers are introduced to describe the ratio of realized exchange to willing exchange, and their dependence on the market price is studied in the cases of shortage and surplus. The realized market surplus, which is the criterion of market efficiency, can be written as a function of the distributions of willing exchange and the rationing rates. With this approach we can strictly prove that a market is efficient in the state of equilibrium.
Statistical energy analysis of nonlinear vibrating systems.
Spelman, G M; Langley, R S
2015-09-28
Nonlinearities in practical systems can arise in contacts between components, possibly from friction or impacts. However, it is also known that quadratic and cubic nonlinearity can occur in the stiffness of structural elements undergoing large amplitude vibration, without the need for local contacts. Nonlinearity due purely to large amplitude vibration can then result in significant energy being found in frequency bands other than those being driven by external forces. To analyse this phenomenon, a method is developed here in which the response of the structure in the frequency domain is divided into frequency bands, and the energy flow between the frequency bands is calculated. The frequency bands are assigned an energy variable to describe the mean response and the nonlinear coupling between bands is described in terms of weighted summations of the convolutions of linear modal transfer functions. This represents a nonlinear extension to an established linear theory known as statistical energy analysis (SEA). The nonlinear extension to SEA theory is presented for the case of a plate structure with quadratic and cubic nonlinearity. PMID:26303923
Statistical analysis of pitting corrosion in condenser tubes
Ault, J.P.; Gehring, G.A. Jr.
1997-12-31
Condenser tube failure via wall penetration allows cooling water to contaminate the working fluid (steam). Contamination, especially from brackish or saltwater, will lower steam quality and thus lower overall plant efficiency. Because of the importance of minimizing leakages, power plant engineers are primarily concerned with the maximum localized corrosion in a unit rather than average corrosion values or rates. Extreme value analysis is a useful tool for evaluating the condition of condenser tubing. Extreme value statistical techniques allow the prediction of the most probable deepest pit in a given surface area based upon data acquired from a smaller surface area. Data is gathered from a physical examination of actual tubes (either in-service or from a sidestream unit) rather than small sample coupons. Three distinct applications of extreme value statistics to condenser tube evaluation are presented in this paper: (1) condition assessment of an operating condenser, (2) design data for material selection, and (3) research tool for assessing impact of various factors on condenser tube corrosion. The projections for operating units based on extreme value analysis are shown to be more useful than those made on the basis of other techniques such as eddy current or electrochemical measurements. Extreme value analysis would benefit from advances in two key areas: (1) development of an accurate and economical method for the measurement of maximum pit depths of condenser tubes in-situ would enhance the application of extreme value statistical analysis to the assessment of condenser tubing corrosion pitting and (2) development of methodologies to predict pit depth-time relationship in addition to pit depth-area relationship would be useful for modeling purposes.
Web-Based Statistical Sampling and Analysis
ERIC Educational Resources Information Center
Quinn, Anne; Larson, Karen
2016-01-01
Consistent with the Common Core State Standards for Mathematics (CCSSI 2010), the authors write that they have asked students to do statistics projects with real data. To obtain real data, their students use the free Web-based app, Census at School, created by the American Statistical Association (ASA) to help promote civic awareness among school…
NASA Astrophysics Data System (ADS)
Andronov, I. L.; Chinarova, L. L.; Kudashkina, L. S.; Marsakova, V. I.; Tkachenko, M. G.
2016-06-01
We have elaborated a set of new algorithms and programs for advanced time series analysis of (generally) multi-component multi-channel observations with irregularly spaced times of observations, which is a common case for large photometric surveys. Previous self-review on these methods for periodogram, scalegram, wavelet, autocorrelation analysis as well as on "running" or "sub-interval" local approximations were self-reviewed in (2003ASPC..292..391A). For an approximation of the phase light curves of nearly-periodic pulsating stars, we use a Trigonometric Polynomial (TP) fit of the statistically optimal degree and initial period improvement using differential corrections (1994OAP.....7...49A). For the determination of parameters of "characteristic points" (minima, maxima, crossings of some constant value etc.) we use a set of methods self-reviewed in 2005ASPC..335...37A, Results of the analysis of the catalogs compiled using these programs are presented in 2014AASP....4....3A. For more complicated signals, we use "phenomenological approximations" with "special shapes" based on functions defined on sub-intervals rather on the complete interval. E. g. for the Algol-type stars we developed the NAV ("New Algol Variable") algorithm (2012Ap.....55..536A, 2012arXiv1212.6707A, 2015JASS...32..127A), which was compared to common methods of Trigonometric Polynomial Fit (TP) or local Algebraic Polynomial (A) fit of a fixed or (alternately) statistically optimal degree. The method allows determine the minimal set of parameters required for the "General Catalogue of Variable Stars", as well as an extended set of phenomenological and astrophysical parameters which may be used for the classification. Totally more that 1900 variable stars were studied in our group using these methods in a frame of the "Inter-Longitude Astronomy" campaign (2010OAP....23....8A) and the "Ukrainian Virtual Observatory" project (2012KPCB...28...85V).
Multivariate statistical analysis of environmental monitoring data
Ross, D.L.
1997-11-01
EPA requires statistical procedures to determine whether soil or ground water adjacent to or below waste units is contaminated. These statistical procedures are often based on comparisons between two sets of data: one representing background conditions, and one representing site conditions. Since statistical requirements were originally promulgated in the 1980s, EPA has made several improvements and modifications. There are, however, problems which remain. One problem is that the regulations do not require a minimum probability that contaminated sites will be correctly identified. Another problems is that the effect of testing several correlated constituents on the probable outcome of the statistical tests has not been quantified. Results from computer simulations to determine power functions for realistic monitoring situations are presented here. Power functions for two different statistical procedures: the Student`s t-test, and the multivariate Hotelling`s T{sup 2} test, are compared. The comparisons indicate that the multivariate test is often more powerful when the tests are applied with significance levels to control the probability of falsely identifying clean sites as contaminated. This program could also be used to verify that statistical procedures achieve some minimum power standard at a regulated waste unit.
[Statistical models for spatial analysis in parasitology].
Biggeri, A; Catelan, D; Dreassi, E; Lagazio, C; Cringoli, G
2004-06-01
The simplest way to study the spatial pattern of a disease is the geographical representation of its cases (or some indicators of them) over a map. Maps based on raw data are generally "wrong" since they do not take into consideration for sampling errors. Indeed, the observed differences between areas (or points in the map) are not directly interpretable, as they derive from the composition of true, structural differences and of the noise deriving from the sampling process. This problem is well known in human epidemiology, and several solutions have been proposed to filter the signal from the noise. These statistical methods are usually referred to as Disease Mapping. In geographical analysis a first goal is to evaluate the statistical significance of the heterogeneity between areas (or points). If the test indicates rejection of the hypothesis of homogeneity the following task is to study the spatial pattern of the disease. The spatial variability of risk is usually decomposed into two terms: a spatially structured (clustering) and a non spatially structured (heterogeneity) one. The heterogeneity term reflects spatial variability due to intrinsic characteristics of the sampling units (e.g. igienic conditions of farms), while the clustering term models the association due to proximity between sampling units, that usually depends on ecological conditions that vary over the study area and that affect in similar way breedings that are close to each other. Hierarchical bayesian models are the main tool to make inference over the clustering and heterogeneity components. The results are based on the marginal posterior distributions of the parameters of the model, that are approximated by Monte Carlo Markov Chain methods. Different models can be defined depending on the terms that are considered, namely a model with only the clustering term, a model with only the heterogeneity term and a model where both are included. Model selection criteria based on a compromise between
Notes on numerical reliability of several statistical analysis programs
Landwehr, J.M.; Tasker, Gary D.
1999-01-01
This report presents a benchmark analysis of several statistical analysis programs currently in use in the USGS. The benchmark consists of a comparison between the values provided by a statistical analysis program for variables in the reference data set ANASTY and their known or calculated theoretical values. The ANASTY data set is an amendment of the Wilkinson NASTY data set that has been used in the statistical literature to assess the reliability (computational correctness) of calculated analytical results.
Statistical Analysis of Refractivity in UAE
NASA Astrophysics Data System (ADS)
Al-Ansari, Kifah; Al-Mal, Abdulhadi Abu; Kamel, Rami
2007-07-01
This paper presents the results of the refractivity statistics in the UAE (United Arab Emirates) for a period of 14 years (1990-2003). Six sites have been considered using meteorological surface data (Abu Dhabi, Dubai, Sharjah, Al-Ain, Ras Al-Kaimah, and Al-Fujairah). Upper air (radiosonde) data were available at one site only, Abu Dhabi airport, which has been considered for the refractivity gradient statistics. Monthly and yearly averages are obtained for the two parameters, refractivity and refractivity gradient. Cumulative distributions are also provided.
ERIC Educational Resources Information Center
Hassan, Mahamood M.; Schwartz, Bill N.
2014-01-01
This paper discusses a student research project that is part of an advanced cost accounting class. The project emphasizes active learning, integrates cost accounting with macroeconomics and statistics by "learning by doing" using real world data. Students analyze sales data for a publicly listed company by focusing on the company's…
ERIC Educational Resources Information Center
McGrath, April L.; Ferns, Alyssa; Greiner, Leigh; Wanamaker, Kayla; Brown, Shelley
2015-01-01
In this study we assessed the usefulness of a multifaceted teaching framework in an advanced statistics course. We sought to expand on past findings by using this framework to assess changes in anxiety and self-efficacy, and we collected focus group data to ascertain whether students attribute such changes to a multifaceted teaching approach.…
ERIC Educational Resources Information Center
Averitt, Sallie D.
This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator…
ERIC Educational Resources Information Center
Billings, Paul H.
This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 6-hour introductory module on statistical process control (SPC), designed to develop competencies in the following skill areas: (1) identification of the three classes of SPC use; (2) understanding a process and how it works; (3)…
Classification of human colonic tissues using FTIR spectra and advanced statistical techniques
NASA Astrophysics Data System (ADS)
Zwielly, A.; Argov, S.; Salman, A.; Bogomolny, E.; Mordechai, S.
2010-04-01
One of the major public health hazards is colon cancer. There is a great necessity to develop new methods for early detection of cancer. If colon cancer is detected and treated early, cure rate of more than 90% can be achieved. In this study we used FTIR microscopy (MSP), which has shown a good potential in the last 20 years in the fields of medical diagnostic and early detection of abnormal tissues. Large database of FTIR microscopic spectra was acquired from 230 human colonic biopsies. Five different subgroups were included in our database, normal and cancer tissues as well as three stages of benign colonic polyps, namely, mild, moderate and severe polyps which are precursors of carcinoma. In this study we applied advanced mathematical and statistical techniques including principal component analysis (PCA) and linear discriminant analysis (LDA), on human colonic FTIR spectra in order to differentiate among the mentioned subgroups' tissues. Good classification accuracy between normal, polyps and cancer groups was achieved with approximately 85% success rate. Our results showed that there is a great potential of developing FTIR-micro spectroscopy as a simple, reagent-free viable tool for early detection of colon cancer in particular the early stages of premalignancy among the benign colonic polyps.
Chen, Zhe; Ohara, Shinji; Cao, Jianting; Vialatte, François; Lenz, Fred A.; Cichocki, Andrzej
2007-01-01
This article is devoted to statistical modeling and analysis of electrocorticogram (ECoG) signals induced by painful cutaneous laser stimuli, which were recorded from implanted electrodes in awake humans. Specifically, with statistical tools of factor analysis and independent component analysis, the pain-induced laser-evoked potentials (LEPs) were extracted and investigated under different controlled conditions. With the help of wavelet analysis, quantitative and qualitative analyses were conducted regarding the LEPs' attributes of power, amplitude, and latency, in both averaging and single-trial experiments. Statistical hypothesis tests were also applied in various experimental setups. Experimental results reported herein also confirm previous findings in the neurophysiology literature. In addition, single-trial analysis has also revealed many new observations that might be interesting to the neuroscientists or clinical neurophysiologists. These promising results show convincing validation that advanced signal processing and statistical analysis may open new avenues for future studies of such ECoG or other relevant biomedical recordings. PMID:18369410
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2015-02-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: (1) P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. (2) Overemphasis on P values rather than on the actual size of the observed effect. (3) Overuse of statistical hypothesis testing, and being seduced by the word "significant". (4) Overreliance on standard errors, which are often misunderstood. PMID:25692012
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2014-11-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason maybe that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1. P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. 2. Overemphasis on P values rather than on the actual size of the observed effect. 3. Overuse of statistical hypothesis testing, and being seduced by the word "significant". 4. Overreliance on standard errors, which are often misunderstood. PMID:25213136
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2014-10-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, however, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1) P-hacking, which is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want; 2) overemphasis on P values rather than on the actual size of the observed effect; 3) overuse of statistical hypothesis testing, and being seduced by the word "significant"; and 4) over-reliance on standard errors, which are often misunderstood. PMID:25204545
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2014-11-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason maybe that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1. P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. 2. Overemphasis on P values rather than on the actual size of the observed effect. 3. Overuse of statistical hypothesis testing, and being seduced by the word "significant". 4. Overreliance on standard errors, which are often misunderstood.
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2014-10-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, however, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1) P-hacking, which is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want; 2) overemphasis on P values rather than on the actual size of the observed effect; 3) overuse of statistical hypothesis testing, and being seduced by the word "significant"; and 4) over-reliance on standard errors, which are often misunderstood.
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2015-02-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: (1) P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. (2) Overemphasis on P values rather than on the actual size of the observed effect. (3) Overuse of statistical hypothesis testing, and being seduced by the word "significant". (4) Overreliance on standard errors, which are often misunderstood.
R: A Software Environment for Comprehensive Statistical Analysis of Astronomical Data
NASA Astrophysics Data System (ADS)
Feigelson, E. D.
2012-09-01
R is the largest public domain software language for statistical analysis of data. Together with CRAN, its rapidly growing collection of >3000 add-on specialized packages, it implements around 60,000 statistical functionalities in a cohesive software environment. Extensive graphical capabilities and interfaces with other programming languages are also available. The scope and language of R/CRAN are briefly described, along with efforts to promulgate its use in the astronomy. R can become an important tool for advanced statistical analysis of astronomical data.
Critical analysis of adsorption data statistically
NASA Astrophysics Data System (ADS)
Kaushal, Achla; Singh, S. K.
2016-09-01
Experimental data can be presented, computed, and critically analysed in a different way using statistics. A variety of statistical tests are used to make decisions about the significance and validity of the experimental data. In the present study, adsorption was carried out to remove zinc ions from contaminated aqueous solution using mango leaf powder. The experimental data was analysed statistically by hypothesis testing applying t test, paired t test and Chi-square test to (a) test the optimum value of the process pH, (b) verify the success of experiment and (c) study the effect of adsorbent dose in zinc ion removal from aqueous solutions. Comparison of calculated and tabulated values of t and χ 2 showed the results in favour of the data collected from the experiment and this has been shown on probability charts. K value for Langmuir isotherm was 0.8582 and m value for Freundlich adsorption isotherm obtained was 0.725, both are <1, indicating favourable isotherms. Karl Pearson's correlation coefficient values for Langmuir and Freundlich adsorption isotherms were obtained as 0.99 and 0.95 respectively, which show higher degree of correlation between the variables. This validates the data obtained for adsorption of zinc ions from the contaminated aqueous solution with the help of mango leaf powder.
GROUNDWATER INFORMATION TRACKING SYSTEM/STATISTICAL ANALYSIS SYSTEM
The Groundwater Information Tracking System with STATistical analysis capability (GRITS/STAT) is a tool designed to facilitate the storage, analysis, and reporting of data collected through groundwater monitoring programs at RCRA, CERCLA, and other regulated facilities an...
Statistical Uncertainty Analysis Applied to Criticality Calculation
Hartini, Entin; Andiwijayakusuma, Dinan; Susmikanti, Mike; Nursinta, A. W.
2010-06-22
In this paper, we present an uncertainty methodology based on a statistical approach, for assessing uncertainties in criticality prediction using monte carlo method due to uncertainties in the isotopic composition of the fuel. The methodology has been applied to criticality calculations with MCNP5 with additional stochastic input of the isotopic fuel composition. The stochastic input were generated using the latin hypercube sampling method based one the probability density function of each nuclide composition. The automatic passing of the stochastic input to the MCNP and the repeated criticality calculation is made possible by using a python script to link the MCNP and our latin hypercube sampling code.
Statistical analysis of life history calendar data.
Eerola, Mervi; Helske, Satu
2016-04-01
The life history calendar is a data-collection tool for obtaining reliable retrospective data about life events. To illustrate the analysis of such data, we compare the model-based probabilistic event history analysis and the model-free data mining method, sequence analysis. In event history analysis, we estimate instead of transition hazards the cumulative prediction probabilities of life events in the entire trajectory. In sequence analysis, we compare several dissimilarity metrics and contrast data-driven and user-defined substitution costs. As an example, we study young adults' transition to adulthood as a sequence of events in three life domains. The events define the multistate event history model and the parallel life domains in multidimensional sequence analysis. The relationship between life trajectories and excess depressive symptoms in middle age is further studied by their joint prediction in the multistate model and by regressing the symptom scores on individual-specific cluster indices. The two approaches complement each other in life course analysis; sequence analysis can effectively find typical and atypical life patterns while event history analysis is needed for causal inquiries.
Statistics over features: EEG signals analysis.
Derya Ubeyli, Elif
2009-08-01
This paper presented the usage of statistics over the set of the features representing the electroencephalogram (EEG) signals. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents, wavelet coefficients and the power levels of power spectral density (PSD) values obtained by eigenvector methods of the EEG signals were used as inputs of the MLPNN trained with Levenberg-Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes. PMID:19555931
Statistical analysis of low level atmospheric turbulence
NASA Technical Reports Server (NTRS)
Tieleman, H. W.; Chen, W. W. L.
1974-01-01
The statistical properties of low-level wind-turbulence data were obtained with the model 1080 total vector anemometer and the model 1296 dual split-film anemometer, both manufactured by Thermo Systems Incorporated. The data obtained from the above fast-response probes were compared with the results obtained from a pair of Gill propeller anemometers. The digitized time series representing the three velocity components and the temperature were each divided into a number of blocks, the length of which depended on the lowest frequency of interest and also on the storage capacity of the available computer. A moving-average and differencing high-pass filter was used to remove the trend and the low frequency components in the time series. The calculated results for each of the anemometers used are represented in graphical or tabulated form.
ERIC Educational Resources Information Center
Petocz, Peter; Sowey, Eric
2012-01-01
The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the statistical…
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Advances and challenges in the attribution of climate impacts using statistical inference
NASA Astrophysics Data System (ADS)
Hsiang, S. M.
2015-12-01
We discuss recent advances, challenges, and debates in the use of statistical models to infer and attribute climate impacts, such as distinguishing effects of "climate" vs. "weather," accounting for simultaneous environmental changes along multiple dimensions, evaluating multiple sources of uncertainty, accounting for adaptation, and simulating counterfactual economic or social trajectories. We relate these ideas to recent findings linking temperature to economic productivity/violence and tropical cyclones to economic growth.
Comparative analysis of positive and negative attitudes toward statistics
NASA Astrophysics Data System (ADS)
Ghulami, Hassan Rahnaward; Ab Hamid, Mohd Rashid; Zakaria, Roslinazairimah
2015-02-01
Many statistics lecturers and statistics education researchers are interested to know the perception of their students' attitudes toward statistics during the statistics course. In statistics course, positive attitude toward statistics is a vital because it will be encourage students to get interested in the statistics course and in order to master the core content of the subject matters under study. Although, students who have negative attitudes toward statistics they will feel depressed especially in the given group assignment, at risk for failure, are often highly emotional, and could not move forward. Therefore, this study investigates the students' attitude towards learning statistics. Six latent constructs have been the measurement of students' attitudes toward learning statistic such as affect, cognitive competence, value, difficulty, interest, and effort. The questionnaire was adopted and adapted from the reliable and validate instrument of Survey of Attitudes towards Statistics (SATS). This study is conducted among engineering undergraduate engineering students in the university Malaysia Pahang (UMP). The respondents consist of students who were taking the applied statistics course from different faculties. From the analysis, it is found that the questionnaire is acceptable and the relationships among the constructs has been proposed and investigated. In this case, students show full effort to master the statistics course, feel statistics course enjoyable, have confidence that they have intellectual capacity, and they have more positive attitudes then negative attitudes towards statistics learning. In conclusion in terms of affect, cognitive competence, value, interest and effort construct the positive attitude towards statistics was mostly exhibited. While negative attitudes mostly exhibited by difficulty construct.
ADVANCED POWER SYSTEMS ANALYSIS TOOLS
Robert R. Jensen; Steven A. Benson; Jason D. Laumb
2001-08-31
The use of Energy and Environmental Research Center (EERC) modeling tools and improved analytical methods has provided key information in optimizing advanced power system design and operating conditions for efficiency, producing minimal air pollutant emissions and utilizing a wide range of fossil fuel properties. This project was divided into four tasks: the demonstration of the ash transformation model, upgrading spreadsheet tools, enhancements to analytical capabilities using the scanning electron microscopy (SEM), and improvements to the slag viscosity model. The ash transformation model, Atran, was used to predict the size and composition of ash particles, which has a major impact on the fate of the combustion system. To optimize Atran key factors such as mineral fragmentation and coalescence, the heterogeneous and homogeneous interaction of the organically associated elements must be considered as they are applied to the operating conditions. The resulting model's ash composition compares favorably to measured results. Enhancements to existing EERC spreadsheet application included upgrading interactive spreadsheets to calculate the thermodynamic properties for fuels, reactants, products, and steam with Newton Raphson algorithms to perform calculations on mass, energy, and elemental balances, isentropic expansion of steam, and gasifier equilibrium conditions. Derivative calculations can be performed to estimate fuel heating values, adiabatic flame temperatures, emission factors, comparative fuel costs, and per-unit carbon taxes from fuel analyses. Using state-of-the-art computer-controlled scanning electron microscopes and associated microanalysis systems, a method to determine viscosity using the incorporation of grey-scale binning acquired by the SEM image was developed. The image analysis capabilities of a backscattered electron image can be subdivided into various grey-scale ranges that can be analyzed separately. Since the grey scale's intensity is
CORSSA: The Community Online Resource for Statistical Seismicity Analysis
Michael, Andrew J.; Wiemer, Stefan
2010-01-01
Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.
Statistical analysis of the 'Almagest' star catalog
NASA Astrophysics Data System (ADS)
Kalashnikov, V. V.; Nosovskii, G. V.; Fomenko, A. T.
The star catalog contained in the 'Almagest', Ptolemy's classical work of astronomy, is examined. An analysis method is proposed which allows the identification of various types of errors committed by the observer. This method not only removes many of the contradictions contained in the catalog but also makes it possible to determine the time period during which the catalog was compiled.
Improved Statistics for Genome-Wide Interaction Analysis
Ueki, Masao; Cordell, Heather J.
2012-01-01
Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new “joint effects” statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al
Improved statistics for genome-wide interaction analysis.
Ueki, Masao; Cordell, Heather J
2012-01-01
Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new "joint effects" statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al
Accuracy Evaluation of a Mobile Mapping System with Advanced Statistical Methods
NASA Astrophysics Data System (ADS)
Toschi, I.; Rodríguez-Gonzálvez, P.; Remondino, F.; Minto, S.; Orlandini, S.; Fuller, A.
2015-02-01
This paper discusses a methodology to evaluate the precision and the accuracy of a commercial Mobile Mapping System (MMS) with advanced statistical methods. So far, the metric potentialities of this emerging mapping technology have been studied in few papers, where generally the assumption that errors follow a normal distribution is made. In fact, this hypothesis should be carefully verified in advance, in order to test how well the Gaussian classic statistics can adapt to datasets that are usually affected by asymmetrical gross errors. The workflow adopted in this study relies on a Gaussian assessment, followed by an outlier filtering process. Finally, non-parametric statistical models are applied, in order to achieve a robust estimation of the error dispersion. Among the different MMSs available on the market, the latest solution provided by RIEGL is here tested, i.e. the VMX-450 Mobile Laser Scanning System. The test-area is the historic city centre of Trento (Italy), selected in order to assess the system performance in dealing with a challenging and historic urban scenario. Reference measures are derived from photogrammetric and Terrestrial Laser Scanning (TLS) surveys. All datasets show a large lack of symmetry that leads to the conclusion that the standard normal parameters are not adequate to assess this type of data. The use of non-normal statistics gives thus a more appropriate description of the data and yields results that meet the quoted a-priori errors.
Importance of data management with statistical analysis set division.
Wang, Ling; Li, Chan-juan; Jiang, Zhi-wei; Xia, Jie-lai
2015-11-01
Testing of hypothesis was affected by statistical analysis set division which was an important data management work before data base lock-in. Objective division of statistical analysis set under blinding was the guarantee of scientific trial conclusion. All the subjects having accepted at least once trial treatment after randomization should be concluded in safety set. Full analysis set should be close to the intention-to-treat as far as possible. Per protocol set division was the most difficult to control in blinded examination because of more subjectivity than the other two. The objectivity of statistical analysis set division must be guaranteed by the accurate raw data, the comprehensive data check and the scientific discussion, all of which were the strict requirement of data management. Proper division of statistical analysis set objectively and scientifically is an important approach to improve the data management quality. PMID:26911044
Importance of data management with statistical analysis set division.
Wang, Ling; Li, Chan-juan; Jiang, Zhi-wei; Xia, Jie-lai
2015-11-01
Testing of hypothesis was affected by statistical analysis set division which was an important data management work before data base lock-in. Objective division of statistical analysis set under blinding was the guarantee of scientific trial conclusion. All the subjects having accepted at least once trial treatment after randomization should be concluded in safety set. Full analysis set should be close to the intention-to-treat as far as possible. Per protocol set division was the most difficult to control in blinded examination because of more subjectivity than the other two. The objectivity of statistical analysis set division must be guaranteed by the accurate raw data, the comprehensive data check and the scientific discussion, all of which were the strict requirement of data management. Proper division of statistical analysis set objectively and scientifically is an important approach to improve the data management quality.
Internet Data Analysis for the Undergraduate Statistics Curriculum
ERIC Educational Resources Information Center
Sanchez, Juana; He, Yan
2005-01-01
Statistics textbooks for undergraduates have not caught up with the enormous amount of analysis of Internet data that is taking place these days. Case studies that use Web server log data or Internet network traffic data are rare in undergraduate Statistics education. And yet these data provide numerous examples of skewed and bimodal…
Guidelines for Statistical Analysis of Percentage of Syllables Stuttered Data
ERIC Educational Resources Information Center
Jones, Mark; Onslow, Mark; Packman, Ann; Gebski, Val
2006-01-01
Purpose: The purpose of this study was to develop guidelines for the statistical analysis of percentage of syllables stuttered (%SS) data in stuttering research. Method; Data on %SS from various independent sources were used to develop a statistical model to describe this type of data. On the basis of this model, %SS data were simulated with…
A Realistic Experimental Design and Statistical Analysis Project
ERIC Educational Resources Information Center
Muske, Kenneth R.; Myers, John A.
2007-01-01
A realistic applied chemical engineering experimental design and statistical analysis project is documented in this article. This project has been implemented as part of the professional development and applied statistics courses at Villanova University over the past five years. The novel aspects of this project are that the students are given a…
System statistical reliability model and analysis
NASA Technical Reports Server (NTRS)
Lekach, V. S.; Rood, H.
1973-01-01
A digital computer code was developed to simulate the time-dependent behavior of the 5-kwe reactor thermoelectric system. The code was used to determine lifetime sensitivity coefficients for a number of system design parameters, such as thermoelectric module efficiency and degradation rate, radiator absorptivity and emissivity, fuel element barrier defect constant, beginning-of-life reactivity, etc. A probability distribution (mean and standard deviation) was estimated for each of these design parameters. Then, error analysis was used to obtain a probability distribution for the system lifetime (mean = 7.7 years, standard deviation = 1.1 years). From this, the probability that the system will achieve the design goal of 5 years lifetime is 0.993. This value represents an estimate of the degradation reliability of the system.
Applications of statistics to medical science, IV survival analysis.
Watanabe, Hiroshi
2012-01-01
The fundamental principles of survival analysis are reviewed. In particular, the Kaplan-Meier method and a proportional hazard model are discussed. This work is the last part of a series in which medical statistics are surveyed.
Advanced materials: Information and analysis needs
Curlee, T.R.; Das, S.; Lee, R.; Trumble, D.
1990-09-01
This report presents the findings of a study to identify the types of information and analysis that are needed for advanced materials. The project was sponsored by the US Bureau of Mines (BOM). It includes a conceptual description of information needs for advanced materials and the development and implementation of a questionnaire on the same subject. This report identifies twelve fundamental differences between advanced and traditional materials and discusses the implications of these differences for data and analysis needs. Advanced and traditional materials differ significantly in terms of physical and chemical properties. Advanced material properties can be customized more easily. The production of advanced materials may differ from traditional materials in terms of inputs, the importance of by-products, the importance of different processing steps (especially fabrication), and scale economies. The potential for change in advanced materials characteristics and markets is greater and is derived from the marriage of radically different materials and processes. In addition to the conceptual study, a questionnaire was developed and implemented to assess the opinions of people who are likely users of BOM information on advanced materials. The results of the questionnaire, which was sent to about 1000 people, generally confirm the propositions set forth in the conceptual part of the study. The results also provide data on the categories of advanced materials and the types of information that are of greatest interest to potential users. 32 refs., 1 fig., 12 tabs.
[Statistical analysis using freely-available "EZR (Easy R)" software].
Kanda, Yoshinobu
2015-10-01
Clinicians must often perform statistical analyses for purposes such evaluating preexisting evidence and designing or executing clinical studies. R is a free software environment for statistical computing. R supports many statistical analysis functions, but does not incorporate a statistical graphical user interface (GUI). The R commander provides an easy-to-use basic-statistics GUI for R. However, the statistical function of the R commander is limited, especially in the field of biostatistics. Therefore, the author added several important statistical functions to the R commander and named it "EZR (Easy R)", which is now being distributed on the following website: http://www.jichi.ac.jp/saitama-sct/. EZR allows the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates and so on, by point-and-click access. In addition, by saving the script automatically created by EZR, users can learn R script writing, maintain the traceability of the analysis, and assure that the statistical process is overseen by a supervisor.
Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers
ERIC Educational Resources Information Center
Keiffer, Greggory L.; Lane, Forrest C.
2016-01-01
Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…
Statistical analysis of litter experiments in teratology
Williams, R.; Buschbom, R.L.
1982-11-01
Teratological data is binary response data (each fetus is either affected or not) in which the responses within a litter are usually not independent. As a result, the litter should be taken as the experimental unit. For each litter, its size, n, and the number of fetuses, x, possessing the effect of interest are recorded. The ratio p = x/n is then the basic data generated by the experiment. There are currently three general approaches to the analysis of teratological data: nonparametric, transformation followed by t-test or ANOVA, and parametric. The first two are currently in wide use by practitioners while the third is relatively new to the field. These first two also appear to possess comparable power levels while maintaining the nominal level of significance. When transformations are employed, care must be exercised to check that the transformed data has the required properties. Since the data is often highly asymmetric, there may be no transformation which renders the data nearly normal. The parametric procedures, including the beta-binomial model, offer the possibility of increased power.
Basic statistical tools in research and data analysis
Ali, Zulfiqar; Bhaskar, S Bala
2016-01-01
Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis. PMID:27729694
The statistical analysis techniques to support the NGNP fuel performance experiments
Binh T. Pham; Jeffrey J. Einerson
2013-10-01
This paper describes the development and application of statistical analysis techniques to support the Advanced Gas Reactor (AGR) experimental program on Next Generation Nuclear Plant (NGNP) fuel performance. The experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel temperature) is regulated by the He–Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the NGNP Data Management and Analysis System for automated processing and qualification of the AGR measured data. The neutronic and thermal code simulation results are used for comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the fuel temperature within a given range.
Advanced analysis methods in particle physics
Bhat, Pushpalatha C.; /Fermilab
2010-10-01
Each generation of high energy physics experiments is grander in scale than the previous - more powerful, more complex and more demanding in terms of data handling and analysis. The spectacular performance of the Tevatron and the beginning of operations of the Large Hadron Collider, have placed us at the threshold of a new era in particle physics. The discovery of the Higgs boson or another agent of electroweak symmetry breaking and evidence of new physics may be just around the corner. The greatest challenge in these pursuits is to extract the extremely rare signals, if any, from huge backgrounds arising from known physics processes. The use of advanced analysis techniques is crucial in achieving this goal. In this review, I discuss the concepts of optimal analysis, some important advanced analysis methods and a few examples. The judicious use of these advanced methods should enable new discoveries and produce results with better precision, robustness and clarity.
A Divergence Statistics Extension to VTK for Performance Analysis.
Pebay, Philippe Pierre; Bennett, Janine Camille
2015-02-01
This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.
Analysis of Coastal Dunes: A Remote Sensing and Statistical Approach.
ERIC Educational Resources Information Center
Jones, J. Richard
1985-01-01
Remote sensing analysis and statistical methods were used to analyze the coastal dunes of Plum Island, Massachusetts. The research methodology used provides an example of a student project for remote sensing, geomorphology, or spatial analysis courses at the university level. (RM)
Advanced nuclear energy analysis technology.
Gauntt, Randall O.; Murata, Kenneth K.; Romero, Vicente JosÔe; Young, Michael Francis; Rochau, Gary Eugene
2004-05-01
A two-year effort focused on applying ASCI technology developed for the analysis of weapons systems to the state-of-the-art accident analysis of a nuclear reactor system was proposed. The Sandia SIERRA parallel computing platform for ASCI codes includes high-fidelity thermal, fluids, and structural codes whose coupling through SIERRA can be specifically tailored to the particular problem at hand to analyze complex multiphysics problems. Presently, however, the suite lacks several physics modules unique to the analysis of nuclear reactors. The NRC MELCOR code, not presently part of SIERRA, was developed to analyze severe accidents in present-technology reactor systems. We attempted to: (1) evaluate the SIERRA code suite for its current applicability to the analysis of next generation nuclear reactors, and the feasibility of implementing MELCOR models into the SIERRA suite, (2) examine the possibility of augmenting ASCI codes or alternatives by coupling to the MELCOR code, or portions thereof, to address physics particular to nuclear reactor issues, especially those facing next generation reactor designs, and (3) apply the coupled code set to a demonstration problem involving a nuclear reactor system. We were successful in completing the first two in sufficient detail to determine that an extensive demonstration problem was not feasible at this time. In the future, completion of this research would demonstrate the feasibility of performing high fidelity and rapid analyses of safety and design issues needed to support the development of next generation power reactor systems.
Advances in clinical analysis 2012.
Couchman, Lewis; Mills, Graham A
2013-01-01
A report on the meeting organized by The Chromatographic Society and the Separation Science Group, Analytical Division of the Royal Society of Chemistry. Over 60 delegates and commercial exhibitors attended this event, held to celebrate the careers of Robert Flanagan and David Perrett, and acknowledge their extensive contributions in the field of clinical analysis. PMID:23330556
Statistical inference in behavior analysis: Friend or foe?
Baron, Alan
1999-01-01
Behavior analysts are undecided about the proper role to be played by inferential statistics in behavioral research. The traditional view, as expressed in Sidman's Tactics of Scientific Research (1960), was that inferential statistics has no place within a science that focuses on the steady-state behavior of individual organisms. Despite this admonition, there have been steady inroads of statistical techniques into behavior analysis since then, as evidenced by publications in the Journal of the Experimental Analysis of Behavior. The issues raised by these developments were considered at a panel held at the 24th annual convention of the Association for Behavior Analysis, Orlando, Florida (May, 1998). The proceedings are reported in this and the following articles. PMID:22478323
Statistical inference in behavior analysis: Experimental control is better
Perone, Michael
1999-01-01
Statistical inference promises automatic, objective, reliable assessments of data, independent of the skills or biases of the investigator, whereas the single-subject methods favored by behavior analysts often are said to rely too much on the investigator's subjective impressions, particularly in the visual analysis of data. In fact, conventional statistical methods are difficult to apply correctly, even by experts, and the underlying logic of null-hypothesis testing has drawn criticism since its inception. By comparison, single-subject methods foster direct, continuous interaction between investigator and subject and development of strong forms of experimental control that obviate the need for statistical inference. Treatment effects are demonstrated in experimental designs that incorporate replication within and between subjects, and the visual analysis of data is adequate when integrated into such designs. Thus, single-subject methods are ideal for shaping—and maintaining—the kind of experimental practices that will ensure the continued success of behavior analysis. PMID:22478328
Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar
Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono
2004-06-01
Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.
Statistical mechanics analysis of thresholding 1-bit compressed sensing
NASA Astrophysics Data System (ADS)
Xu, Yingying; Kabashima, Yoshiyuki
2016-08-01
The one-bit compressed sensing framework aims to reconstruct a sparse signal by only using the sign information of its linear measurements. To compensate for the loss of scale information, past studies in the area have proposed recovering the signal by imposing an additional constraint on the l 2-norm of the signal. Recently, an alternative strategy that captures scale information by introducing a threshold parameter to the quantization process was advanced. In this paper, we analyze the typical behavior of thresholding 1-bit compressed sensing utilizing the replica method of statistical mechanics, so as to gain an insight for properly setting the threshold value. Our result shows that fixing the threshold at a constant value yields better performance than varying it randomly when the constant is optimally tuned, statistically. Unfortunately, the optimal threshold value depends on the statistical properties of the target signal, which may not be known in advance. In order to handle this inconvenience, we develop a heuristic that adaptively tunes the threshold parameter based on the frequency of positive (or negative) values in the binary outputs. Numerical experiments show that the heuristic exhibits satisfactory performance while incurring low computational cost.
Data analysis using the Gnu R system for statistical computation
Simone, James; /Fermilab
2011-07-01
R is a language system for statistical computation. It is widely used in statistics, bioinformatics, machine learning, data mining, quantitative finance, and the analysis of clinical drug trials. Among the advantages of R are: it has become the standard language for developing statistical techniques, it is being actively developed by a large and growing global user community, it is open source software, it is highly portable (Linux, OS-X and Windows), it has a built-in documentation system, it produces high quality graphics and it is easily extensible with over four thousand extension library packages available covering statistics and applications. This report gives a very brief introduction to R with some examples using lattice QCD simulation results. It then discusses the development of R packages designed for chi-square minimization fits for lattice n-pt correlation functions.
ERIC Educational Resources Information Center
Perrett, Jamis J.
2012-01-01
This article demonstrates how textbooks differ in their description of the term "experimental unit". Advanced Placement Statistics teachers and students are often limited in their statistical knowledge by the information presented in their classroom textbook. Definitions and descriptions differ among textbooks as well as among different editions…
A κ-generalized statistical mechanics approach to income analysis
NASA Astrophysics Data System (ADS)
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2009-02-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.
A novel statistic for genome-wide interaction analysis.
Wu, Xuesen; Dong, Hua; Luo, Li; Zhu, Yun; Peng, Gang; Reveille, John D; Xiong, Momiao
2010-09-23
Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001
Statistical Analysis of Tsunamis of the Italian Coasts
Caputo, M.; Faita, G.F.
1982-01-20
A study of a catalog of 138 tsunamis of the Italian coasts has been made. Intensitities of 106 tsunamis has been assigned and cataloged. The statistical analysis of this data fits a density distribution of the form log n = 3.00-0.425 I, where n is the number of tsunamis of intensity I per thousand years.
Introduction to Statistics and Data Analysis With Computer Applications I.
ERIC Educational Resources Information Center
Morris, Carl; Rolph, John
This document consists of unrevised lecture notes for the first half of a 20-week in-house graduate course at Rand Corporation. The chapter headings are: (1) Histograms and descriptive statistics; (2) Measures of dispersion, distance and goodness of fit; (3) Using JOSS for data analysis; (4) Binomial distribution and normal approximation; (5)…
Advanced Placement: Model Policy Components. Policy Analysis
ERIC Educational Resources Information Center
Zinth, Jennifer
2016-01-01
Advanced Placement (AP), launched in 1955 by the College Board as a program to offer gifted high school students the opportunity to complete entry-level college coursework, has since expanded to encourage a broader array of students to tackle challenging content. This Education Commission of the State's Policy Analysis identifies key components of…
Statistical Software for spatial analysis of stratigraphic data sets
2003-04-08
Stratistics s a tool for statistical analysis of spatially explicit data sets and model output for description and for model-data comparisons. lt is intended for the analysis of data sets commonly used in geology, such as gamma ray logs and lithologic sequences, as well as 2-D data such as maps. Stratistics incorporates a far wider range of spatial analysis methods drawn from multiple disciplines, than are currently available in other packages. These include incorporation ofmore » techniques from spatial and landscape ecology, fractal analysis, and mathematical geology. Its use should substantially reduce the risk associated with the use of predictive models« less
Systematic misregistration and the statistical analysis of surface data.
Gee, Andrew H; Treece, Graham M
2014-02-01
Spatial normalisation is a key element of statistical parametric mapping and related techniques for analysing cohort statistics on voxel arrays and surfaces. The normalisation process involves aligning each individual specimen to a template using some sort of registration algorithm. Any misregistration will result in data being mapped onto the template at the wrong location. At best, this will introduce spatial imprecision into the subsequent statistical analysis. At worst, when the misregistration varies systematically with a covariate of interest, it may lead to false statistical inference. Since misregistration generally depends on the specimen's shape, we investigate here the effect of allowing for shape as a confound in the statistical analysis, with shape represented by the dominant modes of variation observed in the cohort. In a series of experiments on synthetic surface data, we demonstrate how allowing for shape can reveal true effects that were previously masked by systematic misregistration, and also guard against misinterpreting systematic misregistration as a true effect. We introduce some heuristics for disentangling misregistration effects from true effects, and demonstrate the approach's practical utility in a case study of the cortical bone distribution in 268 human femurs.
HistFitter software framework for statistical data analysis
NASA Astrophysics Data System (ADS)
Baak, M.; Besjes, G. J.; Côté, D.; Koutsman, A.; Lorenz, J.; Short, D.
2015-04-01
We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface.
Statistical analysis of flight times for space shuttle ferry flights
NASA Technical Reports Server (NTRS)
Graves, M. E.; Perlmutter, M.
1974-01-01
Markov chain and Monte Carlo analysis techniques are applied to the simulated Space Shuttle Orbiter Ferry flights to obtain statistical distributions of flight time duration between Edwards Air Force Base and Kennedy Space Center. The two methods are compared, and are found to be in excellent agreement. The flights are subjected to certain operational and meteorological requirements, or constraints, which cause eastbound and westbound trips to yield different results. Persistence of events theory is applied to the occurrence of inclement conditions to find their effect upon the statistical flight time distribution. In a sensitivity test, some of the constraints are varied to observe the corresponding changes in the results.
[Some basic aspects in statistical analysis of visual acuity data].
Ren, Ze-Qin
2007-06-01
All visual acuity charts used currently have their own shortcomings. Therefore, it is difficult for ophthalmologists to evaluate visual acuity data. Many problems present in the use of statistical methods for handling visual acuity data in clinical research. The quantitative relationship between visual acuity and visual angle varied in different visual acuity charts. The type of visual acuity and visual angle are different from each other. Therefore, different statistical methods should be used for different data sources. A correct understanding and analysis of visual acuity data could be obtained only after the elucidation of these aspects.
Advanced Interval Management: A Benefit Analysis
NASA Technical Reports Server (NTRS)
Timer, Sebastian; Peters, Mark
2016-01-01
This document is the final report for the NASA Langley Research Center (LaRC)- sponsored task order 'Possible Benefits for Advanced Interval Management Operations.' Under this research project, Architecture Technology Corporation performed an analysis to determine the maximum potential benefit to be gained if specific Advanced Interval Management (AIM) operations were implemented in the National Airspace System (NAS). The motivation for this research is to guide NASA decision-making on which Interval Management (IM) applications offer the most potential benefit and warrant further research.
AstroStat-A VO tool for statistical analysis
NASA Astrophysics Data System (ADS)
Kembhavi, A. K.; Mahabal, A. A.; Kale, T.; Jagade, S.; Vibhute, A.; Garg, P.; Vaghmare, K.; Navelkar, S.; Agrawal, T.; Chattopadhyay, A.; Nandrekar, D.; Shaikh, M.
2015-06-01
AstroStat is an easy-to-use tool for performing statistical analysis on data. It has been designed to be compatible with Virtual Observatory (VO) standards thus enabling it to become an integral part of the currently available collection of VO tools. A user can load data in a variety of formats into AstroStat and perform various statistical tests using a menu driven interface. Behind the scenes, all analyses are done using the public domain statistical software-R and the output returned is presented in a neatly formatted form to the user. The analyses performable include exploratory tests, visualizations, distribution fitting, correlation & causation, hypothesis testing, multivariate analysis and clustering. The tool is available in two versions with identical interface and features-as a web service that can be run using any standard browser and as an offline application. AstroStat will provide an easy-to-use interface which can allow for both fetching data and performing power statistical analysis on them.
Using Pre-Statistical Analysis to Streamline Monitoring Assessments
Reed, J.K.
1999-10-20
A variety of statistical methods exist to aid evaluation of groundwater quality and subsequent decision making in regulatory programs. These methods are applied because of large temporal and spatial extrapolations commonly applied to these data. In short, statistical conclusions often serve as a surrogate for knowledge. However, facilities with mature monitoring programs that have generated abundant data have inherently less uncertainty because of the sheer quantity of analytical results. In these cases, statistical tests can be less important, and ''expert'' data analysis should assume an important screening role.The WSRC Environmental Protection Department, working with the General Separations Area BSRI Environmental Restoration project team has developed a method for an Integrated Hydrogeological Analysis (IHA) of historical water quality data from the F and H Seepage Basins groundwater remediation project. The IHA combines common sense analytical techniques and a GIS presentation that force direct interactive evaluation of the data. The IHA can perform multiple data analysis tasks required by the RCRA permit. These include: (1) Development of a groundwater quality baseline prior to remediation startup, (2) Targeting of constituents for removal from RCRA GWPS, (3) Targeting of constituents for removal from UIC, permit, (4) Targeting of constituents for reduced, (5)Targeting of monitoring wells not producing representative samples, (6) Reduction in statistical evaluation, and (7) Identification of contamination from other facilities.
Multivariate statistical analysis of atom probe tomography data.
Parish, Chad M; Miller, Michael K
2010-10-01
The application of spectrum imaging multivariate statistical analysis methods, specifically principal component analysis (PCA), to atom probe tomography (APT) data has been investigated. The mathematical method of analysis is described and the results for two example datasets are analyzed and presented. The first dataset is from the analysis of a PM 2000 Fe-Cr-Al-Ti steel containing two different ultrafine precipitate populations. PCA properly describes the matrix and precipitate phases in a simple and intuitive manner. A second APT example is from the analysis of an irradiated reactor pressure vessel steel. Fine, nm-scale Cu-enriched precipitates having a core-shell structure were identified and qualitatively described by PCA. Advantages, disadvantages, and future prospects for implementing these data analysis methodologies for APT datasets, particularly with regard to quantitative analysis, are also discussed. PMID:20650566
Statistical Analysis of CMC Constituent and Processing Data
NASA Technical Reports Server (NTRS)
Fornuff, Jonathan
2004-01-01
observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)
Statistical analysis and interpolation of compositional data in materials science.
Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M
2015-02-01
Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.
Feature-Based Statistical Analysis of Combustion Simulation Data
Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T
2011-11-18
We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion
2008-01-01
There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754
SMART: Statistical Metabolomics Analysis-An R Tool.
Liang, Yu-Jen; Lin, Yu-Ting; Chen, Chia-Wei; Lin, Chien-Wei; Chao, Kun-Mao; Pan, Wen-Harn; Yang, Hsin-Chou
2016-06-21
Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics Analysis-An R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis. A pharmacometabolomics study of antihypertensive medication was conducted and data were analyzed using SMART. Neuromedin N was identified as a metabolite significantly associated with angiotensin-converting-enzyme inhibitors in our metabolome-wide association analysis (p = 1.56 × 10(-4) in an analysis of covariance (ANCOVA) with an adjustment for unknown latent groups and p = 1.02 × 10(-4) in an ANCOVA with an adjustment for hidden substructures). This endogenous neuropeptide is highly related to neurotensin and neuromedin U, which are involved in blood pressure regulation and smooth muscle contraction. The SMART software, a user guide, and example data can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/metabolomics/SMART.htm .
Building the Community Online Resource for Statistical Seismicity Analysis (CORSSA)
NASA Astrophysics Data System (ADS)
Michael, A. J.; Wiemer, S.; Zechar, J. D.; Hardebeck, J. L.; Naylor, M.; Zhuang, J.; Steacy, S.; Corssa Executive Committee
2010-12-01
Statistical seismology is critical to the understanding of seismicity, the testing of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology - especially to those aspects with great impact on public policy - statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA). CORSSA is a web-based educational platform that is authoritative, up-to-date, prominent, and user-friendly. We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each containing between four and eight articles. The CORSSA web page, www.corssa.org, officially unveiled on September 6, 2010, debuts with an initial set of approximately 10 to 15 articles available online for viewing and commenting with additional articles to be added over the coming months. Each article will be peer-reviewed and will present a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles will include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. A special article will compare and review
CORSSA: Community Online Resource for Statistical Seismicity Analysis
NASA Astrophysics Data System (ADS)
Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.
2011-12-01
Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.
Wavelet analysis in ecology and epidemiology: impact of statistical tests.
Cazelles, Bernard; Cazelles, Kévin; Chavez, Mario
2014-02-01
Wavelet analysis is now frequently used to extract information from ecological and epidemiological time series. Statistical hypothesis tests are conducted on associated wavelet quantities to assess the likelihood that they are due to a random process. Such random processes represent null models and are generally based on synthetic data that share some statistical characteristics with the original time series. This allows the comparison of null statistics with those obtained from original time series. When creating synthetic datasets, different techniques of resampling result in different characteristics shared by the synthetic time series. Therefore, it becomes crucial to consider the impact of the resampling method on the results. We have addressed this point by comparing seven different statistical testing methods applied with different real and simulated data. Our results show that statistical assessment of periodic patterns is strongly affected by the choice of the resampling method, so two different resampling techniques could lead to two different conclusions about the same time series. Moreover, our results clearly show the inadequacy of resampling series generated by white noise and red noise that are nevertheless the methods currently used in the wide majority of wavelets applications. Our results highlight that the characteristics of a time series, namely its Fourier spectrum and autocorrelation, are important to consider when choosing the resampling technique. Results suggest that data-driven resampling methods should be used such as the hidden Markov model algorithm and the 'beta-surrogate' method.
ISSUES IN THE STATISTICAL ANALYSIS OF SMALL-AREA HEALTH DATA. (R825173)
The availability of geographically indexed health and population data, with advances in computing, geographical information systems and statistical methodology, have opened the way for serious exploration of small area health statistics based on routine data. Such analyses may be...
Statistical analysis of single-trial Granger causality spectra.
Brovelli, Andrea
2012-01-01
Granger causality analysis is becoming central for the analysis of interactions between neural populations and oscillatory networks. However, it is currently unclear whether single-trial estimates of Granger causality spectra can be used reliably to assess directional influence. We addressed this issue by combining single-trial Granger causality spectra with statistical inference based on general linear models. The approach was assessed on synthetic and neurophysiological data. Synthetic bivariate data was generated using two autoregressive processes with unidirectional coupling. We simulated two hypothetical experimental conditions: the first mimicked a constant and unidirectional coupling, whereas the second modelled a linear increase in coupling across trials. The statistical analysis of single-trial Granger causality spectra, based on t-tests and linear regression, successfully recovered the underlying pattern of directional influence. In addition, we characterised the minimum number of trials and coupling strengths required for significant detection of directionality. Finally, we demonstrated the relevance for neurophysiology by analysing two local field potentials (LFPs) simultaneously recorded from the prefrontal and premotor cortices of a macaque monkey performing a conditional visuomotor task. Our results suggest that the combination of single-trial Granger causality spectra and statistical inference provides a valuable tool for the analysis of large-scale cortical networks and brain connectivity.
STATISTICAL ANALYSIS OF THE HEAVY NEUTRAL ATOMS MEASURED BY IBEX
Park, Jeewoo; Kucharek, Harald; Möbius, Eberhard; Galli, André; Livadiotis, George; Fuselier, Steve A.; McComas, David J.
2015-10-15
We investigate the directional distribution of heavy neutral atoms in the heliosphere by using heavy neutral maps generated with the IBEX-Lo instrument over three years from 2009 to 2011. The interstellar neutral (ISN) O and Ne gas flow was found in the first-year heavy neutral map at 601 keV and its flow direction and temperature were studied. However, due to the low counting statistics, researchers have not treated the full sky maps in detail. The main goal of this study is to evaluate the statistical significance of each pixel in the heavy neutral maps to get a better understanding of the directional distribution of heavy neutral atoms in the heliosphere. Here, we examine three statistical analysis methods: the signal-to-noise filter, the confidence limit method, and the cluster analysis method. These methods allow us to exclude background from areas where the heavy neutral signal is statistically significant. These methods also allow the consistent detection of heavy neutral atom structures. The main emission feature expands toward lower longitude and higher latitude from the observational peak of the ISN O and Ne gas flow. We call this emission the extended tail. It may be an imprint of the secondary oxygen atoms generated by charge exchange between ISN hydrogen atoms and oxygen ions in the outer heliosheath.
Statistical Analysis of speckle noise reduction techniques for echocardiographic Images
NASA Astrophysics Data System (ADS)
Saini, Kalpana; Dewal, M. L.; Rohit, Manojkumar
2011-12-01
Echocardiography is the safe, easy and fast technology for diagnosing the cardiac diseases. As in other ultrasound images these images also contain speckle noise. In some cases this speckle noise is useful such as in motion detection. But in general noise removal is required for better analysis of the image and proper diagnosis. Different Adaptive and anisotropic filters are included for statistical analysis. Statistical parameters such as Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE) calculated for performance measurement. One more important aspect that there may be blurring during speckle noise removal. So it is prefered that filter should be able to enhance edges during noise removal.
Collagen morphology and texture analysis: from statistics to classification
NASA Astrophysics Data System (ADS)
Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.
2013-07-01
In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.
Statistics in experimental design, preprocessing, and analysis of proteomics data.
Jung, Klaus
2011-01-01
High-throughput experiments in proteomics, such as 2-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS), yield usually high-dimensional data sets of expression values for hundreds or thousands of proteins which are, however, observed on only a relatively small number of biological samples. Statistical methods for the planning and analysis of experiments are important to avoid false conclusions and to receive tenable results. In this chapter, the most frequent experimental designs for proteomics experiments are illustrated. In particular, focus is put on studies for the detection of differentially regulated proteins. Furthermore, issues of sample size planning, statistical analysis of expression levels as well as methods for data preprocessing are covered.
Advanced functional network analysis in the geosciences: The pyunicorn package
NASA Astrophysics Data System (ADS)
Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen
2013-04-01
Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.
Statistical Analysis of the Exchange Rate of Bitcoin.
Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen
2015-01-01
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702
Statistical Analysis of the Exchange Rate of Bitcoin
Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen
2015-01-01
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702
Statistical Analysis of the Exchange Rate of Bitcoin.
Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen
2015-01-01
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.
The statistical analysis of multivariate serological frequency data.
Reyment, Richard A
2005-11-01
Data occurring in the form of frequencies are common in genetics-for example, in serology. Examples are provided by the AB0 group, the Rhesus group, and also DNA data. The statistical analysis of tables of frequencies is carried out using the available methods of multivariate analysis with usually three principal aims. One of these is to seek meaningful relationships between the components of a data set, the second is to examine relationships between populations from which the data have been obtained, the third is to bring about a reduction in dimensionality. This latter aim is usually realized by means of bivariate scatter diagrams using scores computed from a multivariate analysis. The multivariate statistical analysis of tables of frequencies cannot safely be carried out by standard multivariate procedures because they represent compositions and are therefore embedded in simplex space, a subspace of full space. Appropriate procedures for simplex space are compared and contrasted with simple standard methods of multivariate analysis ("raw" principal component analysis). The study shows that the differences between a log-ratio model and a simple logarithmic transformation of proportions may not be very great, particularly as regards graphical ordinations, but important discrepancies do occur. The divergencies between logarithmically based analyses and raw data are, however, great. Published data on Rhesus alleles observed for Italian populations are used to exemplify the subject. PMID:16024067
The statistical analysis of multivariate serological frequency data.
Reyment, Richard A
2005-11-01
Data occurring in the form of frequencies are common in genetics-for example, in serology. Examples are provided by the AB0 group, the Rhesus group, and also DNA data. The statistical analysis of tables of frequencies is carried out using the available methods of multivariate analysis with usually three principal aims. One of these is to seek meaningful relationships between the components of a data set, the second is to examine relationships between populations from which the data have been obtained, the third is to bring about a reduction in dimensionality. This latter aim is usually realized by means of bivariate scatter diagrams using scores computed from a multivariate analysis. The multivariate statistical analysis of tables of frequencies cannot safely be carried out by standard multivariate procedures because they represent compositions and are therefore embedded in simplex space, a subspace of full space. Appropriate procedures for simplex space are compared and contrasted with simple standard methods of multivariate analysis ("raw" principal component analysis). The study shows that the differences between a log-ratio model and a simple logarithmic transformation of proportions may not be very great, particularly as regards graphical ordinations, but important discrepancies do occur. The divergencies between logarithmically based analyses and raw data are, however, great. Published data on Rhesus alleles observed for Italian populations are used to exemplify the subject.
Along-tract statistics allow for enhanced tractography analysis
Colby, John B.; Soderberg, Lindsay; Lebel, Catherine; Dinov, Ivo D.; Thompson, Paul M.; Sowell, Elizabeth R.
2011-01-01
Diffusion imaging tractography is a valuable tool for neuroscience researchers because it allows the generation of individualized virtual dissections of major white matter tracts in the human brain. It facilitates between-subject statistical analyses tailored to the specific anatomy of each participant. There is prominent variation in diffusion imaging metrics (e.g., fractional anisotropy, FA) within tracts, but most tractography studies use a “tract-averaged” approach to analysis by averaging the scalar values from the many streamline vertices in a tract dissection into a single point-spread estimate for each tract. Here we describe a complete workflow needed to conduct an along-tract analysis of white matter streamline tract groups. This consists of 1) A flexible MATLAB toolkit for generating along-tract data based on B-spline resampling and compilation of scalar data at different collections of vertices along the curving tract spines, and 2) Statistical analysis and rich data visualization by leveraging tools available through the R platform for statistical computing. We demonstrate the effectiveness of such an along-tract approach over the tract-averaged approach in an example analysis of 10 major white matter tracts in a single subject. We also show that these techniques easily extend to between-group analyses typically used in neuroscience applications, by conducting an along-tract analysis of differences in FA between 9 individuals with fetal alcohol spectrum disorders (FASDs) and 11 typically-developing controls. This analysis reveals localized differences between FASD and control groups that were not apparent using a tract-averaged method. Finally, to validate our approach and highlight the strength of this extensible software framework, we implement 2 other methods from the literature and leverage the existing workflow tools to conduct a comparison study. PMID:22094644
Multivariate statistical analysis of low-voltage EDS spectrum images
Anderson, I.M.
1998-03-01
Whereas energy-dispersive X-ray spectrometry (EDS) has been used for compositional analysis in the scanning electron microscope for 30 years, the benefits of using low operating voltages for such analyses have been explored only during the last few years. This paper couples low-voltage EDS with two other emerging areas of characterization: spectrum imaging and multivariate statistical analysis. The specimen analyzed for this study was a finished Intel Pentium processor, with the polyimide protective coating stripped off to expose the final active layers.
Advanced Analysis Methods in High Energy Physics
Pushpalatha C. Bhat
2001-10-03
During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.
Advanced Fuel Cycle Economic Sensitivity Analysis
David Shropshire; Kent Williams; J.D. Smith; Brent Boore
2006-12-01
A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.
Advances in statistical methods to map quantitative trait loci in outbred populations.
Hoeschele, I; Uimari, P; Grignola, F E; Zhang, Q; Gage, K M
1997-11-01
Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.
HistFitter: a flexible framework for statistical data analysis
NASA Astrophysics Data System (ADS)
Besjes, G. J.; Baak, M.; Côté, D.; Koutsman, A.; Lorenz, J. M.; Short, D.
2015-12-01
HistFitter is a software framework for statistical data analysis that has been used extensively in the ATLAS Collaboration to analyze data of proton-proton collisions produced by the Large Hadron Collider at CERN. Most notably, HistFitter has become a de-facto standard in searches for supersymmetric particles since 2012, with some usage for Exotic and Higgs boson physics. HistFitter coherently combines several statistics tools in a programmable and flexible framework that is capable of bookkeeping hundreds of data models under study using thousands of generated input histograms. HistFitter interfaces with the statistics tools HistFactory and RooStats to construct parametric models and to perform statistical tests of the data, and extends these tools in four key areas. The key innovations are to weave the concepts of control, validation and signal regions into the very fabric of HistFitter, and to treat these with rigorous methods. Multiple tools to visualize and interpret the results through a simple configuration interface are also provided.
An advanced probabilistic structural analysis method for implicit performance functions
NASA Technical Reports Server (NTRS)
Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.
1989-01-01
In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.
"I am Not a Statistic": Identities of African American Males in Advanced Science Courses
NASA Astrophysics Data System (ADS)
Johnson, Diane Wynn
The United States Bureau of Labor Statistics (2010) expects new industries to generate approximately 2.7 million jobs in science and technology by the year 2018, and there is concern as to whether there will be enough trained individuals to fill these positions. A tremendous resource remains untapped, African American students, especially African American males (National Science Foundation, 2009). Historically, African American males have been omitted from the so called science pipeline. Fewer African American males pursue a science discipline due, in part; to limiting factors they experience in school and at home (Ogbu, 2004). This is a case study of African American males who are enrolled in advanced science courses at a predominantly African American (84%) urban high school. Guided by expectancy-value theory (EVT) of achievement related results (Eccles, 2009; Eccles et al., 1983), twelve African American male students in two advanced science courses were observed in their science classrooms weekly, participated in an in-depth interview, developed a presentation to share with students enrolled in a tenth grade science course, responded to an open-ended identity questionnaire, and were surveyed about their perceptions of school. Additionally, the students' teachers were interviewed, and seven of the students' parents. The interview data analyses highlighted the important role of supportive parents (key socializers) who had high expectations for their sons and who pushed them academically. The students clearly attributed their enrollment in advanced science courses to their high regard for their science teachers, which included positive relationships, hands-on learning in class, and an inviting and encouraging learning environment. Additionally, other family members and coaches played important roles in these young men's lives. Students' PowerPoint(c) presentations to younger high school students on why they should take advanced science courses highlighted these
Statistical analysis of heartbeat data with wavelet techniques
NASA Astrophysics Data System (ADS)
Pazsit, Imre
2004-05-01
The purpose of this paper is to demonstrate the use of some methods of signal analysis, performed on ECG and in some cases blood pressure signals, for the classification of the health status of the heart of mice and rats. Spectral and wavelet analysis were performed on the raw signals. FFT-based coherence and phase was also calculated between blood pressure and raw ECG signals. Finally, RR-intervals were deduced from the ECG signals and an analysis of the fractal dimensions was performed. The analysis was made on data from mice and rats. A correlation was found between the health status of the mice and the rats and some of the statistical descriptors, most notably the phase of the cross-spectra between ECG and blood pressure, and the fractal properties and dimensions of the interbeat series (RR-interval fluctuations).
Cacuci, Dan G.; Ionescu-Bujor, Mihaela
2004-07-15
statistical postprocessing must be repeated anew. In particular, a 'fool-proof' statistical method for correctly analyzing models involving highly correlated parameters does not seem to exist currently, so that particular care must be used when interpreting regression results for such models.By addressing computational issues and particularly challenging open problems and knowledge gaps, this review paper aims at providing a comprehensive basis for further advancements and innovations in the field of sensitivity and uncertainty analysis.
Bayesian statistical analysis of protein side-chain rotamer preferences.
Dunbrack, R. L.; Cohen, F. E.
1997-01-01
We present a Bayesian statistical analysis of the conformations of side chains in proteins from the Protein Data Bank. This is an extension of the backbone-dependent rotamer library, and includes rotamer populations and average chi angles for a full range of phi, psi values. The Bayesian analysis used here provides a rigorous statistical method for taking account of varying amounts of data. Bayesian statistics requires the assumption of a prior distribution for parameters over their range of possible values. This prior distribution can be derived from previous data or from pooling some of the present data. The prior distribution is combined with the data to form the posterior distribution, which is a compromise between the prior distribution and the data. For the chi 2, chi 3, and chi 4 rotamer prior distributions, we assume that the probability of each rotamer type is dependent only on the previous chi rotamer in the chain. For the backbone-dependence of the chi 1 rotamers, we derive prior distributions from the product of the phi-dependent and psi-dependent probabilities. Molecular mechanics calculations with the CHARMM22 potential show a strong similarity with the experimental distributions, indicating that proteins attain their lowest energy rotamers with respect to local backbone-side-chain interactions. The new library is suitable for use in homology modeling, protein folding simulations, and the refinement of X-ray and NMR structures. PMID:9260279
Self-Contained Statistical Analysis of Gene Sets
Cannon, Judy L.; Ricoy, Ulises M.; Johnson, Christopher
2016-01-01
Microarrays are a powerful tool for studying differential gene expression. However, lists of many differentially expressed genes are often generated, and unraveling meaningful biological processes from the lists can be challenging. For this reason, investigators have sought to quantify the statistical probability of compiled gene sets rather than individual genes. The gene sets typically are organized around a biological theme or pathway. We compute correlations between different gene set tests and elect to use Fisher’s self-contained method for gene set analysis. We improve Fisher’s differential expression analysis of a gene set by limiting the p-value of an individual gene within the gene set to prevent a small percentage of genes from determining the statistical significance of the entire set. In addition, we also compute dependencies among genes within the set to determine which genes are statistically linked. The method is applied to T-ALL (T-lineage Acute Lymphoblastic Leukemia) to identify differentially expressed gene sets between T-ALL and normal patients and T-ALL and AML (Acute Myeloid Leukemia) patients. PMID:27711232
Agriculture, population growth, and statistical analysis of the radiocarbon record
Zahid, H. Jabran; Robinson, Erick; Kelly, Robert L.
2016-01-01
The human population has grown significantly since the onset of the Holocene about 12,000 y ago. Despite decades of research, the factors determining prehistoric population growth remain uncertain. Here, we examine measurements of the rate of growth of the prehistoric human population based on statistical analysis of the radiocarbon record. We find that, during most of the Holocene, human populations worldwide grew at a long-term annual rate of 0.04%. Statistical analysis of the radiocarbon record shows that transitioning farming societies experienced the same rate of growth as contemporaneous foraging societies. The same rate of growth measured for populations dwelling in a range of environments and practicing a variety of subsistence strategies suggests that the global climate and/or endogenous biological factors, not adaptability to local environment or subsistence practices, regulated the long-term growth of the human population during most of the Holocene. Our results demonstrate that statistical analyses of large ensembles of radiocarbon dates are robust and valuable for quantitatively investigating the demography of prehistoric human populations worldwide. PMID:26699457
Agriculture, population growth, and statistical analysis of the radiocarbon record.
Zahid, H Jabran; Robinson, Erick; Kelly, Robert L
2016-01-26
The human population has grown significantly since the onset of the Holocene about 12,000 y ago. Despite decades of research, the factors determining prehistoric population growth remain uncertain. Here, we examine measurements of the rate of growth of the prehistoric human population based on statistical analysis of the radiocarbon record. We find that, during most of the Holocene, human populations worldwide grew at a long-term annual rate of 0.04%. Statistical analysis of the radiocarbon record shows that transitioning farming societies experienced the same rate of growth as contemporaneous foraging societies. The same rate of growth measured for populations dwelling in a range of environments and practicing a variety of subsistence strategies suggests that the global climate and/or endogenous biological factors, not adaptability to local environment or subsistence practices, regulated the long-term growth of the human population during most of the Holocene. Our results demonstrate that statistical analyses of large ensembles of radiocarbon dates are robust and valuable for quantitatively investigating the demography of prehistoric human populations worldwide.
Agriculture, population growth, and statistical analysis of the radiocarbon record.
Zahid, H Jabran; Robinson, Erick; Kelly, Robert L
2016-01-26
The human population has grown significantly since the onset of the Holocene about 12,000 y ago. Despite decades of research, the factors determining prehistoric population growth remain uncertain. Here, we examine measurements of the rate of growth of the prehistoric human population based on statistical analysis of the radiocarbon record. We find that, during most of the Holocene, human populations worldwide grew at a long-term annual rate of 0.04%. Statistical analysis of the radiocarbon record shows that transitioning farming societies experienced the same rate of growth as contemporaneous foraging societies. The same rate of growth measured for populations dwelling in a range of environments and practicing a variety of subsistence strategies suggests that the global climate and/or endogenous biological factors, not adaptability to local environment or subsistence practices, regulated the long-term growth of the human population during most of the Holocene. Our results demonstrate that statistical analyses of large ensembles of radiocarbon dates are robust and valuable for quantitatively investigating the demography of prehistoric human populations worldwide. PMID:26699457
Advanced Power Plant Development and Analysis Methodologies
A.D. Rao; G.S. Samuelsen; F.L. Robson; B. Washom; S.G. Berenyi
2006-06-30
Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into advanced power plant systems with goals of achieving high efficiency and minimized environmental impact while using fossil fuels. These power plant concepts include 'Zero Emission' power plants and the 'FutureGen' H2 co-production facilities. The study is broken down into three phases. Phase 1 of this study consisted of utilizing advanced technologies that are expected to be available in the 'Vision 21' time frame such as mega scale fuel cell based hybrids. Phase 2 includes current state-of-the-art technologies and those expected to be deployed in the nearer term such as advanced gas turbines and high temperature membranes for separating gas species and advanced gasifier concepts. Phase 3 includes identification of gas turbine based cycles and engine configurations suitable to coal-based gasification applications and the conceptualization of the balance of plant technology, heat integration, and the bottoming cycle for analysis in a future study. Also included in Phase 3 is the task of acquiring/providing turbo-machinery in order to gather turbo-charger performance data that may be used to verify simulation models as well as establishing system design constraints. The results of these various investigations will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.
Spatial statistical analysis of tree deaths using airborne digital imagery
NASA Astrophysics Data System (ADS)
Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael
2013-04-01
High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).
[Statistical analysis of DNA sequences nearby splicing sites].
Korzinov, O M; Astakhova, T V; Vlasov, P K; Roĭtberg, M A
2008-01-01
Recognition of coding regions within eukaryotic genomes is one of oldest but yet not solved problems of bioinformatics. New high-accuracy methods of splicing sites recognition are needed to solve this problem. A question of current interest is to identify specific features of nucleotide sequences nearby splicing sites and recognize sites in sequence context. We performed a statistical analysis of human genes fragment database and revealed some characteristics of nucleotide sequences in splicing sites neighborhood. Frequencies of all nucleotides and dinucleotides in splicing sites environment were computed and nucleotides and dinucleotides with extremely high\\low occurrences were identified. Statistical information obtained in this work can be used in further development of the methods of splicing sites annotation and exon-intron structure recognition.
Analysis of the Spatial Organization of Molecules with Robust Statistics
Lagache, Thibault; Lang, Gabriel; Sauvonnet, Nathalie; Olivo-Marin, Jean-Christophe
2013-01-01
One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules’ interactions and physical interplay with their environment. The standard tool for analyzing molecules’ distribution statistically is the Ripley’s K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles’ computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters’ size from the maxima of the Ripley’s K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of , which suggests distinct physical mechanisms and cellular functions for each pathway. PMID:24349021
Statistical analysis of subjective preferences for video enhancement
NASA Astrophysics Data System (ADS)
Woods, Russell L.; Satgunam, PremNandhini; Bronstad, P. Matthew; Peli, Eli
2010-02-01
Measuring preferences for moving video quality is harder than for static images due to the fleeting and variable nature of moving video. Subjective preferences for image quality can be tested by observers indicating their preference for one image over another. Such pairwise comparisons can be analyzed using Thurstone scaling (Farrell, 1999). Thurstone (1927) scaling is widely used in applied psychology, marketing, food tasting and advertising research. Thurstone analysis constructs an arbitrary perceptual scale for the items that are compared (e.g. enhancement levels). However, Thurstone scaling does not determine the statistical significance of the differences between items on that perceptual scale. Recent papers have provided inferential statistical methods that produce an outcome similar to Thurstone scaling (Lipovetsky and Conklin, 2004). Here, we demonstrate that binary logistic regression can analyze preferences for enhanced video.
Noise removing in encrypted color images by statistical analysis
NASA Astrophysics Data System (ADS)
Islam, N.; Puech, W.
2012-03-01
Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.
Statistical methods for the detection and analysis of radioactive sources
NASA Astrophysics Data System (ADS)
Klumpp, John
We consider four topics from areas of radioactive statistical analysis in the present study: Bayesian methods for the analysis of count rate data, analysis of energy data, a model for non-constant background count rate distributions, and a zero-inflated model of the sample count rate. The study begins with a review of Bayesian statistics and techniques for analyzing count rate data. Next, we consider a novel system for incorporating energy information into count rate measurements which searches for elevated count rates in multiple energy regions simultaneously. The system analyzes time-interval data in real time to sequentially update a probability distribution for the sample count rate. We then consider a "moving target" model of background radiation in which the instantaneous background count rate is a function of time, rather than being fixed. Unlike the sequential update system, this model assumes a large body of pre-existing data which can be analyzed retrospectively. Finally, we propose a novel Bayesian technique which allows for simultaneous source detection and count rate analysis. This technique is fully compatible with, but independent of, the sequential update system and moving target model.
Bayesian Sensitivity Analysis of Statistical Models with Missing Data
ZHU, HONGTU; IBRAHIM, JOSEPH G.; TANG, NIANSHENG
2013-01-01
Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures. PMID:24753718
On Statistical Analysis of Neuroimages with Imperfect Registration
Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas
2016-01-01
A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168
STATISTICAL ANALYSIS OF TANK 18F FLOOR SAMPLE RESULTS
Harris, S.
2010-09-02
Representative sampling has been completed for characterization of the residual material on the floor of Tank 18F as per the statistical sampling plan developed by Shine [1]. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL [2]. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results [3] to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL{sub 95%}) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 18F. The uncertainty is quantified in this report by an upper 95% confidence limit (UCL{sub 95%}) on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL{sub 95%} was based entirely on the six current scrape sample results (each averaged across three analytical determinations).
STATISTICAL ANALYSIS OF TANK 19F FLOOR SAMPLE RESULTS
Harris, S.
2010-09-02
Representative sampling has been completed for characterization of the residual material on the floor of Tank 19F as per the statistical sampling plan developed by Harris and Shine. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL95%) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current scrape sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 19F. The uncertainty is quantified in this report by an UCL95% on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL95% was based entirely on the six current scrape sample results (each averaged across three analytical determinations).
Goedert, Kelly M.; Boston, Raymond C.; Barrett, A. M.
2013-01-01
Valid research on neglect rehabilitation demands a statistical approach commensurate with the characteristics of neglect rehabilitation data: neglect arises from impairment in distinct brain networks leading to large between-subject variability in baseline symptoms and recovery trajectories. Studies enrolling medically ill, disabled patients, may suffer from missing, unbalanced data, and small sample sizes. Finally, assessment of rehabilitation requires a description of continuous recovery trajectories. Unfortunately, the statistical method currently employed in most studies of neglect treatment [repeated measures analysis of variance (ANOVA), rANOVA] does not well-address these issues. Here we review an alternative, mixed linear modeling (MLM), that is more appropriate for assessing change over time. MLM better accounts for between-subject heterogeneity in baseline neglect severity and in recovery trajectory. MLM does not require complete or balanced data, nor does it make strict assumptions regarding the data structure. Furthermore, because MLM better models between-subject heterogeneity it often results in increased power to observe treatment effects with smaller samples. After reviewing current practices in the field, and the assumptions of rANOVA, we provide an introduction to MLM. We review its assumptions, uses, advantages, and disadvantages. Using real and simulated data, we illustrate how MLM may improve the ability to detect effects of treatment over ANOVA, particularly with the small samples typical of neglect research. Furthermore, our simulation analyses result in recommendations for the design of future rehabilitation studies. Because between-subject heterogeneity is one important reason why studies of neglect treatments often yield conflicting results, employing statistical procedures that model this heterogeneity more accurately will increase the efficiency of our efforts to find treatments to improve the lives of individuals with neglect. PMID
[Advanced data analysis and visualization for clinical laboratory].
Inada, Masanori; Yoneyama, Akiko
2011-01-01
This paper describes visualization techniques that help identify hidden structures in clinical laboratory data. The visualization of data is helpful for a rapid and better understanding of the characteristics of data sets. Various charts help the user identify trends in data. Scatter plots help prevent misinterpretations due to invalid data by identifying outliers. The representation of experimental data in figures is always useful for communicating results to others. Currently, flexible methods such as smoothing methods and latent structure analysis are available owing to the presence of advanced hardware and software. Principle component analysis, which is a well-known technique used to reduce multidimensional data sets, can be carried out on a personal computer. These methods could lead to advanced visualization with regard to exploratory data analysis. In this paper, we present 3 examples in order to introduce advanced data analysis. In the first example, a smoothing spline was fitted to a time-series from the control chart which is not in a state of statistical control. The trend line was clearly extracted from the daily measurements of the control samples. In the second example, principal component analysis was used to identify a new diagnostic indicator for Graves' disease. The multi-dimensional data obtained from patients were reduced to lower dimensions, and the principle components thus obtained summarized the variation in the data set. In the final example, a latent structure analysis for a Gaussian mixture model was used to draw complex density functions suitable for actual laboratory data. As a result, 5 clusters were extracted. The mixed density function of these clusters represented the data distribution graphically. The methods used in the above examples make the creation of complicated models for clinical laboratories more simple and flexible.
ERIC Educational Resources Information Center
McCarthy, Christopher J.; Lambert, Richard G.; Crowe, Elizabeth W.; McCarthy, Colleen J.
2010-01-01
This study examined the relationship of teachers' perceptions of coping resources and demands to job satisfaction factors. Participants were 158 Advanced Placement Statistics high school teachers who completed measures of personal resources for stress prevention, classroom demands and resources, job satisfaction, and intention to leave the field…
ERIC Educational Resources Information Center
Averitt, Sallie D.
This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills in working with line graphs and teaching…
NASA Astrophysics Data System (ADS)
Salman, Ahmad; Lapidot, Itshak; Pomerantz, Ami; Tsror, Leah; Shufan, Elad; Moreh, Raymond; Mordechai, Shaul; Huleihel, Mahmoud
2012-01-01
The early diagnosis of phytopathogens is of a great importance; it could save large economical losses due to crops damaged by fungal diseases, and prevent unnecessary soil fumigation or the use of fungicides and bactericides and thus prevent considerable environmental pollution. In this study, 18 isolates of three different fungi genera were investigated; six isolates of Colletotrichum coccodes, six isolates of Verticillium dahliae and six isolates of Fusarium oxysporum. Our main goal was to differentiate these fungi samples on the level of isolates, based on their infrared absorption spectra obtained using the Fourier transform infrared-attenuated total reflection (FTIR-ATR) sampling technique. Advanced statistical and mathematical methods: principal component analysis (PCA), linear discriminant analysis (LDA), and k-means were applied to the spectra after manipulation. Our results showed significant spectral differences between the various fungi genera examined. The use of k-means enabled classification between the genera with a 94.5% accuracy, whereas the use of PCA [3 principal components (PCs)] and LDA has achieved a 99.7% success rate. However, on the level of isolates, the best differentiation results were obtained using PCA (9 PCs) and LDA for the lower wavenumber region (800-1775 cm-1), with identification success rates of 87%, 85.5%, and 94.5% for Colletotrichum, Fusarium, and Verticillium strains, respectively.
"I am Not a Statistic": Identities of African American Males in Advanced Science Courses
NASA Astrophysics Data System (ADS)
Johnson, Diane Wynn
The United States Bureau of Labor Statistics (2010) expects new industries to generate approximately 2.7 million jobs in science and technology by the year 2018, and there is concern as to whether there will be enough trained individuals to fill these positions. A tremendous resource remains untapped, African American students, especially African American males (National Science Foundation, 2009). Historically, African American males have been omitted from the so called science pipeline. Fewer African American males pursue a science discipline due, in part; to limiting factors they experience in school and at home (Ogbu, 2004). This is a case study of African American males who are enrolled in advanced science courses at a predominantly African American (84%) urban high school. Guided by expectancy-value theory (EVT) of achievement related results (Eccles, 2009; Eccles et al., 1983), twelve African American male students in two advanced science courses were observed in their science classrooms weekly, participated in an in-depth interview, developed a presentation to share with students enrolled in a tenth grade science course, responded to an open-ended identity questionnaire, and were surveyed about their perceptions of school. Additionally, the students' teachers were interviewed, and seven of the students' parents. The interview data analyses highlighted the important role of supportive parents (key socializers) who had high expectations for their sons and who pushed them academically. The students clearly attributed their enrollment in advanced science courses to their high regard for their science teachers, which included positive relationships, hands-on learning in class, and an inviting and encouraging learning environment. Additionally, other family members and coaches played important roles in these young men's lives. Students' PowerPoint(c) presentations to younger high school students on why they should take advanced science courses highlighted these
Statistical energy analysis of complex structures, phase 2
NASA Technical Reports Server (NTRS)
Trudell, R. W.; Yano, L. I.
1980-01-01
A method for estimating the structural vibration properties of complex systems in high frequency environments was investigated. The structure analyzed was the Materials Experiment Assembly, (MEA), which is a portion of the OST-2A payload for the space transportation system. Statistical energy analysis (SEA) techniques were used to model the structure and predict the structural element response to acoustic excitation. A comparison of the intial response predictions and measured acoustic test data is presented. The conclusions indicate that: the SEA predicted the response of primary structure to acoustic excitation over a wide range of frequencies; and the contribution of mechanically induced random vibration to the total MEA is not significant.
Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy
NASA Technical Reports Server (NTRS)
Neergaard, L.; Malone, T.
2001-01-01
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
Statistical design and analysis of RNA sequencing data.
Auer, Paul L; Doerge, R W
2010-06-01
Next-generation sequencing technologies are quickly becoming the preferred approach for characterizing and quantifying entire genomes. Even though data produced from these technologies are proving to be the most informative of any thus far, very little attention has been paid to fundamental design aspects of data collection and analysis, namely sampling, randomization, replication, and blocking. We discuss these concepts in an RNA sequencing framework. Using simulations we demonstrate the benefits of collecting replicated RNA sequencing data according to well known statistical designs that partition the sources of biological and technical variation. Examples of these designs and their corresponding models are presented with the goal of testing differential expression.
Statistical Analysis in Genetic Studies of Mental Illnesses
Zhang, Heping
2011-01-01
Identifying the risk factors for mental illnesses is of significant public health importance. Diagnosis, stigma associated with mental illnesses, comorbidity, and complex etiologies, among others, make it very challenging to study mental disorders. Genetic studies of mental illnesses date back at least a century ago, beginning with descriptive studies based on Mendelian laws of inheritance. A variety of study designs including twin studies, family studies, linkage analysis, and more recently, genomewide association studies have been employed to study the genetics of mental illnesses, or complex diseases in general. In this paper, I will present the challenges and methods from a statistical perspective and focus on genetic association studies. PMID:21909187
Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy
NASA Technical Reports Server (NTRS)
Neergaard, Lynn; Malone, Tina; Gentz, Steven J. (Technical Monitor)
2000-01-01
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
Multi-scale statistical analysis of coronal solar activity
Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.
2016-07-08
Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.
Predicting typology of landslide occurrences by statistical GIS analysis
NASA Astrophysics Data System (ADS)
Mancini, Francesco; Ceppi, Claudia; Ritrovato, Giuliano
2010-05-01
This study aim at the landslide susceptibility mapping by multivariate statistical methods with the additional capability to distinguish among typology of landslide occurrences. The methodology is being tested in a hilly area of the Daunia Region (Apulia, southern Italy) where small settlements are historically threatened by landslide phenomena. In the used multivariate statistical analysis all the variables were managed in a GIS in addition to the landslide inventory where geometric and descriptive properties have to be implemented in a suitable data structure in order to refer the independent set of variables to the typology of landslide occurrences. The independent set of variable selected as possible triggering factors of slope instability phenomena are: elevation, slope, aspect, planform and profile curvature, drained area, lithology, land use, distance from road and river network. The implementation of the landslide inventory was more demanding with respect to a usual multivariate analysis, such as the multiple regression analysis, where the simple presence/absence status of occurrences is being required. According to the classification proposed by Cruden and Varnes, three main landslide typologies were included in the inventory after recognizing by geomorphological survey: a) intermediate to deep-seated compound landslides with failure surface depth > 30m; b) mudslides of shallow to intermediate depth sliding surface; c) deep-seated to intermediate depth rotational landslides with depth of sliding surface < 30m. The inventory implementation constitutes a significant effort supported by the project "Landslide risk assessment for the planning of small urban settlements within chain areas: the case of Daunia" through several expertise. The outcomes of the analysis provide the proneness to landslide, as predicted level of probability, by considering in addition the failure mechanism introduced in the landslide inventory. A map of landslide susceptibility along
Statistical characterization of life drivers for a probabilistic design analysis
NASA Technical Reports Server (NTRS)
Fox, Eric P.; Safie, Fayssal
1992-01-01
This paper discusses the issue of statistical characterization of life drivers for a probabilistic design analysis (PDA) approach to support the conventional deterministic structural design methods that are currently used. The probabilistic approach takes into consideration the modeling inadequacies and uncertainties in many design variables such as loads, environments, and material properties. The importance of the distributional assumption is motivated by illustrating an example where the results differ substantially due to the distribution selected. Different types of distributions are discussed and techniques for estimating the parameters are given. Given this information, procedures are outlined for selecting the appropriate distribution based on the particular type of variable (i.e., dimensional, performance) as well as the information that is available (i.e., test data, engineering analysis). Finally, techniques are given for generating random numbers from these selected distributions within the PDA process.
Detection of bearing damage by statistic vibration analysis
NASA Astrophysics Data System (ADS)
Sikora, E. A.
2016-04-01
The condition of bearings, which are essential components in mechanisms, is crucial to safety. The analysis of the bearing vibration signal, which is always contaminated by certain types of noise, is a very important standard for mechanical condition diagnosis of the bearing and mechanical failure phenomenon. In this paper the method of rolling bearing fault detection by statistical analysis of vibration is proposed to filter out Gaussian noise contained in a raw vibration signal. The results of experiments show that the vibration signal can be significantly enhanced by application of the proposed method. Besides, the proposed method is used to analyse real acoustic signals of a bearing with inner race and outer race faults, respectively. The values of attributes are determined according to the degree of the fault. The results confirm that the periods between the transients, which represent bearing fault characteristics, can be successfully detected.
Vibroacoustic optimization using a statistical energy analysis model
NASA Astrophysics Data System (ADS)
Culla, Antonio; D`Ambrogio, Walter; Fregolent, Annalisa; Milana, Silvia
2016-08-01
In this paper, an optimization technique for medium-high frequency dynamic problems based on Statistical Energy Analysis (SEA) method is presented. Using a SEA model, the subsystem energies are controlled by internal loss factors (ILF) and coupling loss factors (CLF), which in turn depend on the physical parameters of the subsystems. A preliminary sensitivity analysis of subsystem energy to CLF's is performed to select CLF's that are most effective on subsystem energies. Since the injected power depends not only on the external loads but on the physical parameters of the subsystems as well, it must be taken into account under certain conditions. This is accomplished in the optimization procedure, where approximate relationships between CLF's, injected power and physical parameters are derived. The approach is applied on a typical aeronautical structure: the cabin of a helicopter.
Statistical learning analysis in neuroscience: aiming for transparency.
Hanke, Michael; Halchenko, Yaroslav O; Haxby, James V; Pollmann, Stefan
2010-01-01
Encouraged by a rise of reciprocal interest between the machine learning and neuroscience communities, several recent studies have demonstrated the explanatory power of statistical learning techniques for the analysis of neural data. In order to facilitate a wider adoption of these methods, neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures. We argue that such transparency requires "neuroscience-aware" technology for the performance of multivariate pattern analyses of neural data that can be documented in a comprehensive, yet comprehensible way. Recently, we introduced PyMVPA, a specialized Python framework for machine learning based data analysis that addresses this demand. Here, we review its features and applicability to various neural data modalities. PMID:20582270
First statistical analysis of Geant4 quality software metrics
NASA Astrophysics Data System (ADS)
Ronchieri, Elisabetta; Grazia Pia, Maria; Giacomini, Francesco
2015-12-01
Geant4 is a simulation system of particle transport through matter, widely used in several experimental areas from high energy physics and nuclear experiments to medical studies. Some of its applications may involve critical use cases; therefore they would benefit from an objective assessment of the software quality of Geant4. In this paper, we provide a first statistical evaluation of software metrics data related to a set of Geant4 physics packages. The analysis aims at identifying risks for Geant4 maintainability, which would benefit from being addressed at an early stage. The findings of this pilot study set the grounds for further extensions of the analysis to the whole of Geant4 and to other high energy physics software systems.
Statistical analysis of cascading failures in power grids
Chertkov, Michael; Pfitzner, Rene; Turitsyn, Konstantin
2010-12-01
We introduce a new microscopic model of cascading failures in transmission power grids. This model accounts for automatic response of the grid to load fluctuations that take place on the scale of minutes, when optimum power flow adjustments and load shedding controls are unavailable. We describe extreme events, caused by load fluctuations, which cause cascading failures of loads, generators and lines. Our model is quasi-static in the causal, discrete time and sequential resolution of individual failures. The model, in its simplest realization based on the Directed Current description of the power flow problem, is tested on three standard IEEE systems consisting of 30, 39 and 118 buses. Our statistical analysis suggests a straightforward classification of cascading and islanding phases in terms of the ratios between average number of removed loads, generators and links. The analysis also demonstrates sensitivity to variations in line capacities. Future research challenges in modeling and control of cascading outages over real-world power networks are discussed.
FRATS: Functional Regression Analysis of DTI Tract Statistics
Zhu, Hongtu; Styner, Martin; Tang, Niansheng; Liu, Zhexing; Lin, Weili; Gilmore, John H.
2010-01-01
Diffusion tensor imaging (DTI) provides important information on the structure of white matter fiber bundles as well as detailed tissue properties along these fiber bundles in vivo. This paper presents a functional regression framework, called FRATS, for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The functional regression framework consists of four integrated components: the local polynomial kernel method for smoothing multiple diffusion properties along individual fiber bundles, a functional linear model for characterizing the association between fiber bundle diffusion properties and a set of covariates, a global test statistic for testing hypotheses of interest, and a resampling method for approximating the p-value of the global test statistic. The proposed methodology is applied to characterizing the development of five diffusion properties including fractional anisotropy, mean diffusivity, and the three eigenvalues of diffusion tensor along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. Significant age and gestational age effects on the five diffusion properties were found in both tracts. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. PMID:20335089
Design and statistical analysis of oral medicine studies: common pitfalls.
Baccaglini, L; Shuster, J J; Cheng, J; Theriaque, D W; Schoenbach, V J; Tomar, S L; Poole, C
2010-04-01
A growing number of articles are emerging in the medical and statistics literature that describe epidemiologic and statistical flaws of research studies. Many examples of these deficiencies are encountered in the oral, craniofacial, and dental literature. However, only a handful of methodologic articles have been published in the oral literature warning investigators of potential errors that may arise early in the study and that can irreparably bias the final results. In this study, we briefly review some of the most common pitfalls that our team of epidemiologists and statisticians has identified during the review of submitted or published manuscripts and research grant applications. We use practical examples from the oral medicine and dental literature to illustrate potential shortcomings in the design and analysis of research studies, and how these deficiencies may affect the results and their interpretation. A good study design is essential, because errors in the analysis can be corrected if the design was sound, but flaws in study design can lead to data that are not salvageable. We recommend consultation with an epidemiologist or a statistician during the planning phase of a research study to optimize study efficiency, minimize potential sources of bias, and document the analytic plan.
Catalkaya, Ebru Cokay; Kargi, Fikret
2007-09-01
Advanced oxidation of diuron in aqueous solution by Fenton's reagent using FeSO(4) as source of Fe(II) was investigated in the absence of light. Effects of operating parameters namely the concentrations of pesticide (diuron), H(2)O(2) and Fe(II) on oxidation of diuron was investigated by using Box-Behnken statistical experiment design and the surface response analysis. Diuron oxidation by the Fenton reagent was evaluated by determining the total organic carbon (TOC), diuron, and adsorbable organic halogen (AOX) removals. Concentration ranges of the reagents resulting in the highest level of diuron oxidation were determined. Diuron removal increased with increasing H(2)O(2) and Fe(II) concentrations up to a certain level. Diuron concentration had a more profound effect than H(2)O(2) and Fe(II) in removal of diuron, TOC and AOX from the aqueous solution. Nearly complete (98.5%) disappearance of diuron was achieved after 15min reaction period. However, only 58% of diuron was mineralized after 240min under optimal operating conditions indicating formation of some intermediate products. Optimal H(2)O(2)/Fe(II)/diuron ratio resulting in the maximum diuron removal (98.5%) was found to be 302/38/20 (mgl(-1)).
The Statistical Analysis Techniques to Support the NGNP Fuel Performance Experiments
Bihn T. Pham; Jeffrey J. Einerson
2010-06-01
This paper describes the development and application of statistical analysis techniques to support the AGR experimental program on NGNP fuel performance. The experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel/graphite temperature) is regulated by the He-Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the SAS-based NGNP Data Management and Analysis System (NDMAS) for automated processing and qualification of the AGR measured data. The NDMAS also stores daily neutronic (power) and thermal (heat transfer) code simulation results along with the measurement data, allowing for their combined use and comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the target quantity (fuel temperature) within a given range.
Statistical Analysis of Surface Water Quality Data of Eastern Massachusetts
NASA Astrophysics Data System (ADS)
Andronache, C.; Hon, R.; Tedder, N.; Xian, Q.; Schaudt, B.
2008-05-01
We present a characterization of current state of surface water, changes in time and dependence on land use, precipitation regime, and possible other natural and human influences based on data from the USGS National Water Quality Assessment (NAWQA) Program for New England streams. Time series analysis is used to detect changes and relationship with discharge and precipitation regime. Statistical techniques are employed to analyze relationships among multiple chemical variable monitored. Analysis of ion concentrations reveals information about possible natural sources and processes, and anthropogenic influences. A notable example is the increase in salt concentration in ground and surface waters, with impact on drinking water quality. Salt concentration increase in water can be linked to road salt usage during winters with heavy snowfall and other factors. Road salt enters water supplies by percolation through soil into groundwater or runoff and drainage into reservoirs. After entering fast-flowing streams, rivers and lakes, salt runoff concentrations are rapidly diluted. Road salt infiltration is more common for groundwater-based supplies, such as wells, springs, and reservoirs that are recharged mainly by groundwater. We use principal component analysis and other statistical procedures to obtain a description of the dominant independent variables that influence the observed chemical compositional range. In most cases, over 85 percent of the total variation can be explained by 3 to 4 components. The overwhelming variation is attributed to a large compositional range of Na and Cl seen even if all data are combined into a single dataset. Na versus Cl correlation coefficients are commonly greater than 0.9. Second components are typically associated with dilutions by overland flows (non winter months) and/or increased concentrations due to evaporation (summer season) or overland flows (winter season) if a snow storm is followed by the application of deicers on road
Advancing Behavior Analysis in Zoos and Aquariums.
Maple, Terry L; Segura, Valerie D
2015-05-01
Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers.
Advancing Behavior Analysis in Zoos and Aquariums.
Maple, Terry L; Segura, Valerie D
2015-05-01
Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers. PMID:27540508
Statistical Scalability Analysis of Communication Operations in Distributed Applications
Vetter, J S; McCracken, M O
2001-02-27
Current trends in high performance computing suggest that users will soon have widespread access to clusters of multiprocessors with hundreds, if not thousands, of processors. This unprecedented degree of parallelism will undoubtedly expose scalability limitations in existing applications, where scalability is the ability of a parallel algorithm on a parallel architecture to effectively utilize an increasing number of processors. Users will need precise and automated techniques for detecting the cause of limited scalability. This paper addresses this dilemma. First, we argue that users face numerous challenges in understanding application scalability: managing substantial amounts of experiment data, extracting useful trends from this data, and reconciling performance information with their application's design. Second, we propose a solution to automate this data analysis problem by applying fundamental statistical techniques to scalability experiment data. Finally, we evaluate our operational prototype on several applications, and show that statistical techniques offer an effective strategy for assessing application scalability. In particular, we find that non-parametric correlation of the number of tasks to the ratio of the time for individual communication operations to overall communication time provides a reliable measure for identifying communication operations that scale poorly.
Statistical analysis of the autoregressive modeling of reverberant speech.
Gaubitch, Nikolay D; Ward, Darren B; Naylor, Patrick A
2006-12-01
Hands-free speech input is required in many modern telecommunication applications that employ autoregressive (AR) techniques such as linear predictive coding. When the hands-free input is obtained in enclosed reverberant spaces such as typical office rooms, the speech signal is distorted by the room transfer function. This paper utilizes theoretical results from statistical room acoustics to analyze the AR modeling of speech under these reverberant conditions. Three cases are considered: (i) AR coefficients calculated from a single observation; (ii) AR coefficients calculated jointly from an M-channel observation (M > 1); and (iii) AR coefficients calculated from the output of a delay-and sum beamformer. The statistical analysis, with supporting simulations, shows that the spatial expectation of the AR coefficients for cases (i) and (ii) are approximately equal to those from the original speech, while for case (iii) there is a discrepancy due to spatial correlation between the microphones which can be significant. It is subsequently demonstrated that at each individual source-microphone position (without spatial expectation), the M-channel AR coefficients from case (ii) provide the best approximation to the clean speech coefficients when microphones are closely spaced (<0.3m). PMID:17225429
Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results
NASA Technical Reports Server (NTRS)
Meuer, Hans-Werner; Simon, Horst D.; Strohmeier, Erich; Lasinski, T. A. (Technical Monitor)
1994-01-01
In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.
Constraining cosmology with shear peak statistics: tomographic analysis
NASA Astrophysics Data System (ADS)
Martinet, Nicolas; Bartlett, James G.; Kiessling, Alina; Sartoris, Barbara
2015-09-01
The abundance of peaks in weak gravitational lensing maps is a potentially powerful cosmological tool, complementary to measurements of the shear power spectrum. We study peaks detected directly in shear maps, rather than convergence maps, an approach that has the advantage of working directly with the observable quantity, the galaxy ellipticity catalog. Using large numbers of numerical simulations to accurately predict the abundance of peaks and their covariance, we quantify the cosmological constraints attainable by a large-area survey similar to that expected from the Euclid mission, focusing on the density parameter, Ωm, and on the power spectrum normalization, σ8, for illustration. We present a tomographic peak counting method that improves the conditional (marginal) constraints by a factor of 1.2 (2) over those from a two-dimensional (i.e., non-tomographic) peak-count analysis. We find that peak statistics provide constraints an order of magnitude less accurate than those from the cluster sample in the ideal situation of a perfectly known observable-mass relation; however, when the scaling relation is not known a priori, the shear-peak constraints are twice as strong and orthogonal to the cluster constraints, highlighting the value of using both clusters and shear-peak statistics.
Statistical analysis of test data for APM rod issue
Edwards, T.B.; Harris, S.P.; Reeve, C.P.
1992-05-01
The uncertainty associated with the use of the K-Reactor axial power monitors (APMs) to measure roof-top-ratios is investigated in this report. Internal heating test data acquired under both DC-flow conditions and AC-flow conditions have been analyzed. These tests were conducted to simulate gamma heating at the lower power levels planned for reactor operation. The objective of this statistical analysis is to investigate the relationship between the observed and true roof-top-ratio (RTR) values and associated uncertainties at power levels within this lower operational range. Conditional on a given, known power level, a prediction interval for the true RTR value corresponding to a new, observed RTR is given. This is done for a range of power levels. Estimates of total system uncertainty are also determined by combining the analog-to-digital converter uncertainty with the results from the test data.
Statistical models of video structure for content analysis and characterization.
Vasconcelos, N; Lippman, A
2000-01-01
Content structure plays an important role in the understanding of video. In this paper, we argue that knowledge about structure can be used both as a means to improve the performance of content analysis and to extract features that convey semantic information about the content. We introduce statistical models for two important components of this structure, shot duration and activity, and demonstrate the usefulness of these models with two practical applications. First, we develop a Bayesian formulation for the shot segmentation problem that is shown to extend the standard thresholding model in an adaptive and intuitive way, leading to improved segmentation accuracy. Second, by applying the transformation into the shot duration/activity feature space to a database of movie clips, we also illustrate how the Bayesian model captures semantic properties of the content. We suggest ways in which these properties can be used as a basis for intuitive content-based access to movie libraries.
Statistical analysis of a carcinogen mixture experiment. I. Liver carcinogens.
Elashoff, R M; Fears, T R; Schneiderman, M A
1987-09-01
This paper describes factorial experiments designed to determine whether 2 liver carcinogens act synergistically to produce liver cancers in Fischer 344 rats. Four hepatocarcinogens, cycad flour, lasiocarpine (CAS: 303-34-4), aflatoxin B1 (CAS: 1162-65-8), and dipentylnitrosamine (CAS: 13256-06-9), were studied in pairwise combinations. Each of the 6 possible pairs was studied by means of 4 X 4 factorial experiment, each agent being fed at zero and at 3 non-zero doses. Methods of analysis designed explicitly for this study were derived to study interaction. These methods were supplemented by standard statistical methods appropriate for one-at-a-time studies. Antagonism was not discovered in any chemical mixture. Some chemical mixtures did interact synergistically. Findings for male and female animals were generally, but not always, in agreement.
Barcode localization with region based gradient statistical analysis
NASA Astrophysics Data System (ADS)
Chen, Zhiyuan; Zhao, Yuming
2015-03-01
Barcode, as a kind of data representation method, has been adopted in a wide range of areas. Especially with the rise of the smart phone and the hand-held device equipped with high resolution camera and great computation power, barcode technique has found itself more extensive applications. In industrial field, barcode reading system is highly demanded to be robust to blur, illumination change, pitch, rotation, and scale change. This paper gives a new idea in localizing barcode under a region-based gradient statistical analysis. Making this idea as the basis, four algorithms have been developed for dealing with Linear, PDF417, Stacked 1D1D and Stacked 1D2D barcodes respectively. After being evaluated on our challenging dataset with more than 17000 images, the result shows that our methods can achieve an average localization accuracy of 82.17% with respect to 8 kinds of distortions and within an average time of 12 ms.
Statistical analysis of arch shape with conic sections.
Sampson, P D
1983-06-01
Arcs of conic sections are used to model the shapes of human dental arches and to provide a basis for the statistical and graphical analysis of a population of shapes. The Bingham distribution, an elliptical distribution on a hypersphere, is applied in order to model the coefficients of the conic arcs. It provides a definition of an 'average shape' and it quantifies variation in shape. Geometric envelopes of families of conic arcs whose coefficients satisfy a quadratic constraint are used to depict the distribution of shapes in the plane and to make graphical inferences about the average shape. The methods are demonstrated with conic arcs fitted to a sample of 66 maxillary dental arches.
Dental arch shape: a statistical analysis using conic sections.
Sampson, P D
1981-05-01
This report addresses two problems in the study of the shape of human dental arches; (1) the description of arch shape by mathematical functions and (2) the description of variation among the dental arch shapes in a population. A new algorithm for fitting conic sections is used to model the maxillary dental arches of a sample of sixty-six subjects. A statistical model for shapes represented by arcs of conic sections is demonstrated on the sample of sixty-six dental arches. It permits the definition of an "average shape" and the graphic representation of variation in shape. The model and methods of analysis presented should help dental scientists to better define and quantify "normal" or "ideal" shapes and "normal ranges of variation" for the shape of the dental arch.
ERIC Educational Resources Information Center
Heaviside, Sheila; And Others
The "Survey of Advanced Telecommunications in U.S. Public Elementary and Secondary Schools, Fall 1996" collected information from 911 regular United States public elementary and secondary schools regarding the availability and use of advanced telecommunications, and in particular, access to the Internet, plans to obtain Internet access, use of…
A statistical analysis of the daily streamflow hydrograph
NASA Astrophysics Data System (ADS)
Kavvas, M. L.; Delleur, J. W.
1984-03-01
In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.
Spectral signature verification using statistical analysis and text mining
NASA Astrophysics Data System (ADS)
DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.
2016-05-01
In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is
NASA Astrophysics Data System (ADS)
Ruggles, Adam J.
2015-11-01
This paper presents improved statistical insight regarding the self-similar scalar mixing process of atmospheric hydrogen jets and the downstream region of under-expanded hydrogen jets. Quantitative planar laser Rayleigh scattering imaging is used to probe both jets. The self-similarity of statistical moments up to the sixth order (beyond the literature established second order) is documented in both cases. This is achieved using a novel self-similar normalization method that facilitated a degree of statistical convergence that is typically limited to continuous, point-based measurements. This demonstrates that image-based measurements of a limited number of samples can be used for self-similar scalar mixing studies. Both jets exhibit the same radial trends of these moments demonstrating that advanced atmospheric self-similarity can be applied in the analysis of under-expanded jets. Self-similar histograms away from the centerline are shown to be the combination of two distributions. The first is attributed to turbulent mixing. The second, a symmetric Poisson-type distribution centered on zero mass fraction, progressively becomes the dominant and eventually sole distribution at the edge of the jet. This distribution is attributed to shot noise-affected pure air measurements, rather than a diffusive superlayer at the jet boundary. This conclusion is reached after a rigorous measurement uncertainty analysis and inspection of pure air data collected with each hydrogen data set. A threshold based upon the measurement noise analysis is used to separate the turbulent and pure air data, and thusly estimate intermittency. Beta-distributions (four parameters) are used to accurately represent the turbulent distribution moments. This combination of measured intermittency and four-parameter beta-distributions constitutes a new, simple approach to model scalar mixing. Comparisons between global moments from the data and moments calculated using the proposed model show excellent
Statistical Signal Analysis for Systems with Interferenced Inputs
NASA Technical Reports Server (NTRS)
Bai, R. M.; Mielnicka-Pate, A. L.
1985-01-01
A new approach is introduced, based on statistical signal analysis, which overcomes the error due to input signal interference. The model analyzed is given. The input signals u sub 1 (t) and u sub 2 (t) are assumed to be unknown. The measurable signals x sub 1 (t) and x sub 2 (t) are interferened according to the frequency response functions, H sub 12 (f) and H sub 21 (f). The goal of the analysis was to evaluate the power output due to each input, u sub 1 (t) and u sub 2 (t), for the case where both are applied to the same time. In addition, all frequency response functions are calculated. The interferenced system is described by a set of five equations with six unknown functions. An IBM XT Personal Computer, which was interfaced with the FFT, was used to solve the set of equations. The software was tested on an electrical two-input, one-output system. The results were excellent. The research presented includes the analysis of the acoustic radiation from a rectangular plate with two force inputs and the sound pressure as an output signal.
Statistical analysis and modelling of small satellite reliability
NASA Astrophysics Data System (ADS)
Guo, Jian; Monas, Liora; Gill, Eberhard
2014-05-01
This paper attempts to characterize failure behaviour of small satellites through statistical analysis of actual in-orbit failures. A unique Small Satellite Anomalies Database comprising empirical failure data of 222 small satellites has been developed. A nonparametric analysis of the failure data has been implemented by means of a Kaplan-Meier estimation. An innovative modelling method, i.e. Bayesian theory in combination with Markov Chain Monte Carlo (MCMC) simulations, has been proposed to model the reliability of small satellites. An extensive parametric analysis using the Bayesian/MCMC method has been performed to fit a Weibull distribution to the data. The influence of several characteristics such as the design lifetime, mass, launch year, mission type and the type of satellite developers on the reliability has been analyzed. The results clearly show the infant mortality of small satellites. Compared with the classical maximum-likelihood estimation methods, the proposed Bayesian/MCMC method results in better fitting Weibull models and is especially suitable for reliability modelling where only very limited failures are observed.
Helioseismology of pre-emerging active regions. III. Statistical analysis
Barnes, G.; Leka, K. D.; Braun, D. C.; Birch, A. C.
2014-05-01
The subsurface properties of active regions (ARs) prior to their appearance at the solar surface may shed light on the process of AR formation. Helioseismic holography has been applied to samples taken from two populations of regions on the Sun (pre-emergence and without emergence), each sample having over 100 members, that were selected to minimize systematic bias, as described in Paper I. Paper II showed that there are statistically significant signatures in the average helioseismic properties that precede the formation of an AR. This paper describes a more detailed analysis of the samples of pre-emergence regions and regions without emergence based on discriminant analysis. The property that is best able to distinguish the populations is found to be the surface magnetic field, even a day before the emergence time. However, after accounting for the correlations between the surface field and the quantities derived from helioseismology, there is still evidence of a helioseismic precursor to AR emergence that is present for at least a day prior to emergence, although the analysis presented cannot definitively determine the subsurface properties prior to emergence due to the small sample sizes.
Classification of Malaysia aromatic rice using multivariate statistical analysis
Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A.; Omar, O.
2015-05-15
Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.
Classification of Malaysia aromatic rice using multivariate statistical analysis
NASA Astrophysics Data System (ADS)
Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A.; Omar, O.
2015-05-01
Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC-MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.
Advanced Technology Lifecycle Analysis System (ATLAS)
NASA Technical Reports Server (NTRS)
O'Neil, Daniel A.; Mankins, John C.
2004-01-01
Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is
Statistical analysis of nonlinear dynamical systems using differential geometric sampling methods.
Calderhead, Ben; Girolami, Mark
2011-12-01
Mechanistic models based on systems of nonlinear differential equations can help provide a quantitative understanding of complex physical or biological phenomena. The use of such models to describe nonlinear interactions in molecular biology has a long history; however, it is only recently that advances in computing have allowed these models to be set within a statistical framework, further increasing their usefulness and binding modelling and experimental approaches more tightly together. A probabilistic approach to modelling allows us to quantify uncertainty in both the model parameters and the model predictions, as well as in the model hypotheses themselves. In this paper, the Bayesian approach to statistical inference is adopted and we examine the significant challenges that arise when performing inference over nonlinear ordinary differential equation models describing cell signalling pathways and enzymatic circadian control; in particular, we address the difficulties arising owing to strong nonlinear correlation structures, high dimensionality and non-identifiability of parameters. We demonstrate how recently introduced differential geometric Markov chain Monte Carlo methodology alleviates many of these issues by making proposals based on local sensitivity information, which ultimately allows us to perform effective statistical analysis. Along the way, we highlight the deep link between the sensitivity analysis of such dynamic system models and the underlying Riemannian geometry of the induced posterior probability distributions. PMID:23226584
ERIC Educational Resources Information Center
Pearson, Kathryn
2008-01-01
Macquarie University Library was concerned at the length of time that elapsed between placement of an interlibrary loan request to the satisfaction of that request. Taking advantage of improved statistical information available to them through membership of the CLIC Consortium, library staff investigated the reasons for delivery delay. This led to…
Statistical Analysis of Tank 5 Floor Sample Results
Shine, E. P.
2013-01-31
Sampling has been completed for the characterization of the residual material on the floor of Tank 5 in the F-Area Tank Farm at the Savannah River Site (SRS), near Aiken, SC. The sampling was performed by Savannah River Remediation (SRR) LLC using a stratified random sampling plan with volume-proportional compositing. The plan consisted of partitioning the residual material on the floor of Tank 5 into three non-overlapping strata: two strata enclosed accumulations, and a third stratum consisted of a thin layer of material outside the regions of the two accumulations. Each of three composite samples was constructed from five primary sample locations of residual material on the floor of Tank 5. Three of the primary samples were obtained from the stratum containing the thin layer of material, and one primary sample was obtained from each of the two strata containing an accumulation. This report documents the statistical analyses of the analytical results for the composite samples. The objective of the analysis is to determine the mean concentrations and upper 95% confidence (UCL95) bounds for the mean concentrations for a set of analytes in the tank residuals. The statistical procedures employed in the analyses were consistent with the Environmental Protection Agency (EPA) technical guidance by Singh and others [2010]. Savannah River National Laboratory (SRNL) measured the sample bulk density, nonvolatile beta, gross alpha, and the radionuclide1, elemental, and chemical concentrations three times for each of the composite samples. The analyte concentration data were partitioned into three separate groups for further analysis: analytes with every measurement above their minimum detectable concentrations (MDCs), analytes with no measurements above their MDCs, and analytes with a mixture of some measurement results above and below their MDCs. The means, standard deviations, and UCL95s were computed for the analytes in the two groups that had at least some measurements
Statistical Analysis Of Tank 5 Floor Sample Results
Shine, E. P.
2012-08-01
Sampling has been completed for the characterization of the residual material on the floor of Tank 5 in the F-Area Tank Farm at the Savannah River Site (SRS), near Aiken, SC. The sampling was performed by Savannah River Remediation (SRR) LLC using a stratified random sampling plan with volume-proportional compositing. The plan consisted of partitioning the residual material on the floor of Tank 5 into three non-overlapping strata: two strata enclosed accumulations, and a third stratum consisted of a thin layer of material outside the regions of the two accumulations. Each of three composite samples was constructed from five primary sample locations of residual material on the floor of Tank 5. Three of the primary samples were obtained from the stratum containing the thin layer of material, and one primary sample was obtained from each of the two strata containing an accumulation. This report documents the statistical analyses of the analytical results for the composite samples. The objective of the analysis is to determine the mean concentrations and upper 95% confidence (UCL95) bounds for the mean concentrations for a set of analytes in the tank residuals. The statistical procedures employed in the analyses were consistent with the Environmental Protection Agency (EPA) technical guidance by Singh and others [2010]. Savannah River National Laboratory (SRNL) measured the sample bulk density, nonvolatile beta, gross alpha, and the radionuclide, elemental, and chemical concentrations three times for each of the composite samples. The analyte concentration data were partitioned into three separate groups for further analysis: analytes with every measurement above their minimum detectable concentrations (MDCs), analytes with no measurements above their MDCs, and analytes with a mixture of some measurement results above and below their MDCs. The means, standard deviations, and UCL95s were computed for the analytes in the two groups that had at least some measurements
STATISTICAL ANALYSIS OF TANK 5 FLOOR SAMPLE RESULTS
Shine, E.
2012-03-14
Sampling has been completed for the characterization of the residual material on the floor of Tank 5 in the F-Area Tank Farm at the Savannah River Site (SRS), near Aiken, SC. The sampling was performed by Savannah River Remediation (SRR) LLC using a stratified random sampling plan with volume-proportional compositing. The plan consisted of partitioning the residual material on the floor of Tank 5 into three non-overlapping strata: two strata enclosed accumulations, and a third stratum consisted of a thin layer of material outside the regions of the two accumulations. Each of three composite samples was constructed from five primary sample locations of residual material on the floor of Tank 5. Three of the primary samples were obtained from the stratum containing the thin layer of material, and one primary sample was obtained from each of the two strata containing an accumulation. This report documents the statistical analyses of the analytical results for the composite samples. The objective of the analysis is to determine the mean concentrations and upper 95% confidence (UCL95) bounds for the mean concentrations for a set of analytes in the tank residuals. The statistical procedures employed in the analyses were consistent with the Environmental Protection Agency (EPA) technical guidance by Singh and others [2010]. Savannah River National Laboratory (SRNL) measured the sample bulk density, nonvolatile beta, gross alpha, radionuclide, inorganic, and anion concentrations three times for each of the composite samples. The analyte concentration data were partitioned into three separate groups for further analysis: analytes with every measurement above their minimum detectable concentrations (MDCs), analytes with no measurements above their MDCs, and analytes with a mixture of some measurement results above and below their MDCs. The means, standard deviations, and UCL95s were computed for the analytes in the two groups that had at least some measurements above their
A statistical design for testing apomictic diversification through linkage analysis.
Zeng, Yanru; Hou, Wei; Song, Shuang; Feng, Sisi; Shen, Lin; Xia, Guohua; Wu, Rongling
2014-03-01
The capacity of apomixis to generate maternal clones through seed reproduction has made it a useful characteristic for the fixation of heterosis in plant breeding. It has been observed that apomixis displays pronounced intra- and interspecific diversification, but the genetic mechanisms underlying this diversification remains elusive, obstructing the exploitation of this phenomenon in practical breeding programs. By capitalizing on molecular information in mapping populations, we describe and assess a statistical design that deploys linkage analysis to estimate and test the pattern and extent of apomictic differences at various levels from genotypes to species. The design is based on two reciprocal crosses between two individuals each chosen from a hermaphrodite or monoecious species. A multinomial distribution likelihood is constructed by combining marker information from two crosses. The EM algorithm is implemented to estimate the rate of apomixis and test its difference between two plant populations or species as the parents. The design is validated by computer simulation. A real data analysis of two reciprocal crosses between hickory (Carya cathayensis) and pecan (C. illinoensis) demonstrates the utilization and usefulness of the design in practice. The design provides a tool to address fundamental and applied questions related to the evolution and breeding of apomixis.
A statistical method for draft tube pressure pulsation analysis
NASA Astrophysics Data System (ADS)
Doerfler, P. K.; Ruchonnet, N.
2012-11-01
Draft tube pressure pulsation (DTPP) in Francis turbines is composed of various components originating from different physical phenomena. These components may be separated because they differ by their spatial relationships and by their propagation mechanism. The first step for such an analysis was to distinguish between so-called synchronous and asynchronous pulsations; only approximately periodic phenomena could be described in this manner. However, less regular pulsations are always present, and these become important when turbines have to operate in the far off-design range, in particular at very low load. The statistical method described here permits to separate the stochastic (random) component from the two traditional 'regular' components. It works in connection with the standard technique of model testing with several pressure signals measured in draft tube cone. The difference between the individual signals and the averaged pressure signal, together with the coherence between the individual pressure signals is used for analysis. An example reveals that a generalized, non-periodic version of the asynchronous pulsation is important at low load.
Data Analysis & Statistical Methods for Command File Errors
NASA Technical Reports Server (NTRS)
Meshkat, Leila; Waggoner, Bruce; Bryant, Larry
2014-01-01
This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.
Autotasked Performance in the NAS Workload: A Statistical Analysis
NASA Technical Reports Server (NTRS)
Carter, R. L.; Stockdale, I. E.; Kutler, Paul (Technical Monitor)
1998-01-01
A statistical analysis of the workload performance of a production quality FORTRAN code for five different Cray Y-MP hardware and system software configurations is performed. The analysis was based on an experimental procedure that was designed to minimize correlations between the number of requested CPUs and the time of day the runs were initiated. Observed autotasking over heads were significantly larger for the set of jobs that requested the maximum number of CPUs. Speedups for UNICOS 6 releases show consistent wall clock speedups in the workload of around 2. which is quite good. The observed speed ups were very similar for the set of jobs that requested 8 CPUs and the set that requested 4 CPUs. The original NAS algorithm for determining charges to the user discourages autotasking in the workload. A new charging algorithm to be applied to jobs run in the NQS multitasking queues also discourages NAS users from using auto tasking. The new algorithm favors jobs requesting 8 CPUs over those that request less, although the jobs requesting 8 CPUs experienced significantly higher over head and presumably degraded system throughput. A charging algorithm is presented that has the following desirable characteristics when applied to the data: higher overhead jobs requesting 8 CPUs are penalized when compared to moderate overhead jobs requesting 4 CPUs, thereby providing a charging incentive to NAS users to use autotasking in a manner that provides them with significantly improved turnaround while also maintaining system throughput.
Advanced techniques in current signature analysis
Smith, S.F.; Castleberry, K.N.
1992-03-01
In general, both ac and dc motors can be characterized as weakly nonlinear systems, in which both linear and nonlinear effects occur simultaneously. Fortunately, the nonlinearities are generally well behaved and understood and an be handled via several standard mathematical techniques already well developed in the systems modeling area; examples are piecewise linear approximations and Volterra series representations. Field measurements of numerous motors and motor-driven systems confirm the rather complex nature of motor current spectra and illustrate both linear and nonlinear effects (including line harmonics and modulation components). Although previous current signature analysis (CSA) work at Oak Ridge and other sites has principally focused on the modulation mechanisms and detection methods (AM, PM, and FM), more recent studies have been conducted on linear spectral components (those appearing in the electric current at their actual frequencies and not as modulation sidebands). For example, large axial-flow compressors ({approximately}3300 hp) in the US gaseous diffusion uranium enrichment plants exhibit running-speed ({approximately}20 Hz) and high-frequency vibrational information (>1 kHz) in their motor current spectra. Several signal-processing techniques developed to facilitate analysis of these components, including specialized filtering schemes, are presented. Finally, concepts for the designs of advanced digitally based CSA units are offered, which should serve to foster the development of much more computationally capable ``smart`` CSA instrumentation in the next several years. 3 refs.
External quality assessment in water microbiology: statistical analysis of performance.
Tillett, H E; Lightfoot, N F; Eaton, S
1993-04-01
A UK-based scheme of water microbiology assessment requires participants to record counts of relevant organisms. Not every sample will contain the target number of organisms because of natural variation and therefore a range of results is acceptable. Results which are tail-end (i.e. at the extreme low or high end of this range) could occasionally be reported by any individual laboratory by chance. Several tail-end results might imply a laboratory problem. Statistical assessment is done in two stages. A non-parametric test of the distribution of tail-end counts amongst laboratories is performed (Cochran's Q) and, if they are not random, then observed and expected frequencies of tail-end counts are compared to identify participants who may have reported excessive numbers of low or high results. Analyses so far have shown that laboratories find high counts no more frequently than would be expected by chance, but that significant clusters of low counts can be detected among participants. These findings have been observed both in short-term and in long-term assessments, thus allowing detection of new episodes of poor performance and intermittent problems. The analysis relies on an objective definition of tail-end results. Working definitions are presented which should identify poor performance in terms of microbiological significance, and which allow fair comparison between membrane-filtration and multiple-tube techniques. Smaller differences between laboratories, which may be statistically significant, will not be detected. Different definitions of poor performance could be incorporated into future assessments.
Statistical Analysis of Data with Non-Detectable Values
Frome, E.L.
2004-08-26
Environmental exposure measurements are, in general, positive and may be subject to left censoring, i.e. the measured value is less than a ''limit of detection''. In occupational monitoring, strategies for assessing workplace exposures typically focus on the mean exposure level or the probability that any measurement exceeds a limit. A basic problem of interest in environmental risk assessment is to determine if the mean concentration of an analyte is less than a prescribed action level. Parametric methods, used to determine acceptable levels of exposure, are often based on a two parameter lognormal distribution. The mean exposure level and/or an upper percentile (e.g. the 95th percentile) are used to characterize exposure levels, and upper confidence limits are needed to describe the uncertainty in these estimates. In certain situations it is of interest to estimate the probability of observing a future (or ''missed'') value of a lognormal variable. Statistical methods for random samples (without non-detects) from the lognormal distribution are well known for each of these situations. In this report, methods for estimating these quantities based on the maximum likelihood method for randomly left censored lognormal data are described and graphical methods are used to evaluate the lognormal assumption. If the lognormal model is in doubt and an alternative distribution for the exposure profile of a similar exposure group is not available, then nonparametric methods for left censored data are used. The mean exposure level, along with the upper confidence limit, is obtained using the product limit estimate, and the upper confidence limit on the 95th percentile (i.e. the upper tolerance limit) is obtained using a nonparametric approach. All of these methods are well known but computational complexity has limited their use in routine data analysis with left censored data. The recent development of the R environment for statistical data analysis and graphics has greatly
Spectral signature verification using statistical analysis and text mining
NASA Astrophysics Data System (ADS)
DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.
2016-05-01
In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two diﬀerent aspects of a spectral signature to arrive at a ﬁnal qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is
ERIC Educational Resources Information Center
Petocz, Agnes; Newbery, Glenn
2010-01-01
Statistics education in psychology often falls disappointingly short of its goals. The increasing use of qualitative approaches in statistics education research has extended and enriched our understanding of statistical cognition processes, and thus facilitated improvements in statistical education and practices. Yet conceptual analysis, a…
Advanced Coal Wind Hybrid: Economic Analysis
Phadke, Amol; Goldman, Charles; Larson, Doug; Carr, Tom; Rath, Larry; Balash, Peter; Yih-Huei, Wan
2008-11-28
Growing concern over climate change is prompting new thinking about the technologies used to generate electricity. In the future, it is possible that new government policies on greenhouse gas emissions may favor electric generation technology options that release zero or low levels of carbon emissions. The Western U.S. has abundant wind and coal resources. In a world with carbon constraints, the future of coal for new electrical generation is likely to depend on the development and successful application of new clean coal technologies with near zero carbon emissions. This scoping study explores the economic and technical feasibility of combining wind farms with advanced coal generation facilities and operating them as a single generation complex in the Western US. The key questions examined are whether an advanced coal-wind hybrid (ACWH) facility provides sufficient advantages through improvements to the utilization of transmission lines and the capability to firm up variable wind generation for delivery to load centers to compete effectively with other supply-side alternatives in terms of project economics and emissions footprint. The study was conducted by an Analysis Team that consists of staff from the Lawrence Berkeley National Laboratory (LBNL), National Energy Technology Laboratory (NETL), National Renewable Energy Laboratory (NREL), and Western Interstate Energy Board (WIEB). We conducted a screening level analysis of the economic competitiveness and technical feasibility of ACWH generation options located in Wyoming that would supply electricity to load centers in California, Arizona or Nevada. Figure ES-1 is a simple stylized representation of the configuration of the ACWH options. The ACWH consists of a 3,000 MW coal gasification combined cycle power plant equipped with carbon capture and sequestration (G+CC+CCS plant), a fuel production or syngas storage facility, and a 1,500 MW wind plant. The ACWH project is connected to load centers by a 3,000 MW
Hydrogeochemical characteristics of groundwater in Latvia using multivariate statistical analysis
NASA Astrophysics Data System (ADS)
Retike, Inga; Kalvans, Andis; Bikse, Janis; Popovs, Konrads; Babre, Alise
2015-04-01
The aim of this study is to determine geochemical processes denoting trace element levels and variations in the fresh groundwater in Latvia. The database of 1398 groundwater samples containing records about major ion chemistry, trace elements and geological conditions was made and used. Accuracy of groundwater analysis and errors were determined and excluded prior statistical analysis. Groundwater hydrogeochemical groups were distributed on the basis of major ion concentrations using Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The results of PCA showed that there are three main geochemical groups explaining 84% of the total variance in data set. Component 1 explains the greatest amount of variance- 51% with main positive loadings of Cl, Na, K and Mg. Component 2 explains 21% of the variance with highest loadings of HCO3, Ca and Mg. Component 3 shows the highest loadings of SO4 and Ca and explains 12% of the total variance. HCA was chosen because of its great ability to group large amount of data (groundwater samples) in several clusters based on similar characteristics. As a result three large groups comprising nine distinctive clusters was made. It was possible to characterise each cluster depending on its depth of sampling, aquifer material and geochemical processes: carbonate dissolution (weathering), groundwater mixing, gypsum dissolution, ion exchange and seawater and upward saline water intrusion. Cluster 1 is the least altered infiltration water with very low load of dissolved salts. It is concluded that the groundwater in Cluster 5 has evolved from Cluster 1 by carbonate weathering in an open system conditions. The Cluster 4 is similar to Cluster 5, yet have been affected by reduction of sulphates and iron species. Cluster 3 is characterised by highest loading of chloride salts while Cluster 9 represents groundwater with highest sulphate concentrations resulting from gypsum dissolution. However, Cluster 8 is an intermediate
Common pitfalls in statistical analysis: Intention-to-treat versus per-protocol analysis
Ranganathan, Priya; Pramesh, C. S.; Aggarwal, Rakesh
2016-01-01
During the conduct of clinical trials, it is not uncommon to have protocol violations or inability to assess outcomes. This article in our series on common pitfalls in statistical analysis explains the complexities of analyzing results from such trials and highlights the importance of “intention-to-treat” analysis. PMID:27453832
Metrology Optical Power Budgeting in SIM Using Statistical Analysis Techniques
NASA Technical Reports Server (NTRS)
Kuan, Gary M
2008-01-01
The Space Interferometry Mission (SIM) is a space-based stellar interferometry instrument, consisting of up to three interferometers, which will be capable of micro-arc second resolution. Alignment knowledge of the three interferometer baselines requires a three-dimensional, 14-leg truss with each leg being monitored by an external metrology gauge. In addition, each of the three interferometers requires an internal metrology gauge to monitor the optical path length differences between the two sides. Both external and internal metrology gauges are interferometry based, operating at a wavelength of 1319 nanometers. Each gauge has fiber inputs delivering measurement and local oscillator (LO) power, split into probe-LO and reference-LO beam pairs. These beams experience power loss due to a variety of mechanisms including, but not restricted to, design efficiency, material attenuation, element misalignment, diffraction, and coupling efficiency. Since the attenuation due to these sources may degrade over time, an accounting of the range of expected attenuation is needed so an optical power margin can be book kept. A method of statistical optical power analysis and budgeting, based on a technique developed for deep space RF telecommunications, is described in this paper and provides a numerical confidence level for having sufficient optical power relative to mission metrology performance requirements.
Statistical Analysis of the AIAA Drag Prediction Workshop CFD Solutions
NASA Technical Reports Server (NTRS)
Morrison, Joseph H.; Hemsch, Michael J.
2007-01-01
The first AIAA Drag Prediction Workshop (DPW), held in June 2001, evaluated the results from an extensive N-version test of a collection of Reynolds-Averaged Navier-Stokes CFD codes. The code-to-code scatter was more than an order of magnitude larger than desired for design and experimental validation of cruise conditions for a subsonic transport configuration. The second AIAA Drag Prediction Workshop, held in June 2003, emphasized the determination of installed pylon-nacelle drag increments and grid refinement studies. The code-to-code scatter was significantly reduced compared to the first DPW, but still larger than desired. However, grid refinement studies showed no significant improvement in code-to-code scatter with increasing grid refinement. The third AIAA Drag Prediction Workshop, held in June 2006, focused on the determination of installed side-of-body fairing drag increments and grid refinement studies for clean attached flow on wing alone configurations and for separated flow on the DLR-F6 subsonic transport model. This report compares the transonic cruise prediction results of the second and third workshops using statistical analysis.
Statistical analysis of mission profile parameters of civil transport airplanes
NASA Technical Reports Server (NTRS)
Buxbaum, O.
1972-01-01
The statistical analysis of flight times as well as airplane gross weights and fuel weights of jet-powered civil transport airplanes has shown that the distributions of their frequency of occurrence per flight can be presented approximately in general form. Before, however, these results may be used during the project stage of an airplane for defining a typical mission profile (the parameters of which are assumed to occur, for example, with a probability of 50 percent), the following points have to be taken into account. Because the individual airplanes were rotated during service, the scatter between the distributions of mission profile parameters for airplanes of the same type, which were flown with similar payload, has proven to be very small. Significant deviations from the generalized distributions may occur if an operator uses one airplane preferably on one or two specific routes. Another reason for larger deviations could be that the maintenance services of the operators of the observed airplanes are not representative of other airlines. Although there are indications that this is unlikely, similar information should be obtained from other operators. Such information would improve the reliability of the data.
Statistical Analysis of Resistivity Anomalies Caused by Underground Caves
NASA Astrophysics Data System (ADS)
Frid, V.; Averbach, A.; Frid, M.; Dudkinski, D.; Liskevich, G.
2015-05-01
Geophysical prospecting of underground caves being performed on a construction site is often still a challenging procedure. Estimation of a likelihood level of an anomaly found is frequently a mandatory requirement of a project principal due to necessity of risk/safety assessment. However, the methodology of such estimation is not hitherto developed. Aiming to put forward such a methodology the present study (being performed as a part of an underground caves mapping prior to the land development on the site area) consisted of application of electrical resistivity tomography (ERT) together with statistical analysis utilized for the likelihood assessment of underground anomalies located. The methodology was first verified via a synthetic modeling technique and applied to the in situ collected ERT data and then crossed referenced with intrusive investigations (excavation and drilling) for the data verification. The drilling/excavation results showed that the proper discovering of underground caves can be done if anomaly probability level is not lower than 90 %. Such a probability value was shown to be consistent with the modeling results. More than 30 underground cavities were discovered on the site utilizing the methodology.
Plutonium metal exchange program : current status and statistical analysis
Tandon, L.; Eglin, J. L.; Michalak, S. E.; Picard, R. R.; Temer, D. J.
2004-01-01
The Rocky Flats Plutonium (Pu) Metal Sample Exchange program was conducted to insure the quality and intercomparability of measurements such as Pu assay, Pu isotopics, and impurity analyses. The Rocky Flats program was discontinued in 1989 after more than 30 years. In 2001, Los Alamos National Laboratory (LANL) reestablished the Pu Metal Exchange program. In addition to the Atomic Weapons Establishment (AWE) at Aldermaston, six Department of Energy (DOE) facilities Argonne East, Argonne West, Livermore, Los Alamos, New Brunswick Laboratory, and Savannah River are currently participating in the program. Plutonium metal samples are prepared and distributed to the sites for destructive measurements to determine elemental concentration, isotopic abundance, and both metallic and nonmetallic impurity levels. The program provides independent verification of analytical measurement capabilies for each participating facility and allows problems in analytical methods to be identified. The current status of the program will be discussed with emphasis on the unique statistical analysis and modeling of the data developed for the program. The discussion includes the definition of the consensus values for each analyte (in the presence and absence of anomalous values and/or censored values), and interesting features of the data and the results.
Measurement of Plethysmogram and Statistical Method for Analysis
NASA Astrophysics Data System (ADS)
Shimizu, Toshihiro
The plethysmogram is measured at different points of human body by using the photo interrupter, which sensitively depends on the physical and mental situation of human body. In this paper the statistical method of the data-analysis is investigated to discuss the dependence of plethysmogram on stress and aging. The first one is the representation method based on the return map, which provides usuful information for the waveform, the flucuation in phase and the fluctuation in amplitude. The return map method makes it possible to understand the fluctuation of plethymogram in amplitude and in phase more clearly and globally than in the conventional power spectrum method. The second is the Lisajous plot and the correlation function to analyze the phase difference between the plethysmograms of the right finger tip and of the left finger tip. The third is the R-index, from which we can estimate “the age of the blood flow”. The R-index is defined by the global character of plethysmogram, which is different from the usual APG-index. The stress- and age-dependence of plethysmogram is discussed by using these methods.
Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis
Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad
2015-10-02
Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.
Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint
Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad
2015-12-08
Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.
Slow and fast solar wind - data selection and statistical analysis
NASA Astrophysics Data System (ADS)
Wawrzaszek, Anna; Macek, Wiesław M.; Bruno, Roberto; Echim, Marius
2014-05-01
In this work we consider the important problem of selection of slow and fast solar wind data measured in-situ by the Ulysses spacecraft during two solar minima (1995-1997, 2007-2008) and solar maximum (1999-2001). To recognise different types of solar wind we use a set of following parameters: radial velocity, proton density, proton temperature, the distribution of charge states of oxygen ions, and compressibility of magnetic field. We present how this idea of the data selection works on Ulysses data. In the next step we consider the chosen intervals for fast and slow solar wind and perform statistical analysis of the fluctuating magnetic field components. In particular, we check the possibility of identification of inertial range by considering the scale dependence of the third and fourth orders scaling exponents of structure function. We try to verify the size of inertial range depending on the heliographic latitudes, heliocentric distance and phase of the solar cycle. Research supported by the European Community's Seventh Framework Programme (FP7/2007 - 2013) under grant agreement no 313038/STORM.
A Statistical Aggregation Engine for Climatology and Trend Analysis
NASA Astrophysics Data System (ADS)
Chapman, D. R.; Simon, T. A.; Halem, M.
2014-12-01
Fundamental climate data records (FCDRs) from satellite instruments often span tens to hundreds of terabytes or even petabytes in scale. These large volumes make it difficult to aggregate or summarize their climatology and climate trends. It is especially cumbersome to supply the full derivation (provenance) of these aggregate calculations. We present a lightweight and resilient software platform, Gridderama that simplifies the calculation of climatology by exploiting the "Data-Cube" topology often present in earth observing satellite records. By using the large array storage (LAS) paradigm, Gridderama allows the analyst to more easily produce a series of aggregate climate data products at progressively coarser spatial and temporal resolutions. Furthermore, provenance tracking and extensive visualization capabilities allow the analyst to track down and correct for data problems such as missing data and outliers that may impact the scientific results. We have developed and applied Gridderama to calculate a trend analysis of 55 Terabytes of AIRS Level 1b infrared radiances, and show statistically significant trending in the greenhouse gas absorption bands as observed by AIRS over the 2003-2012 decade. We will extend this calculation to show regional changes in CO2 concentration from AIRS over the 2003-2012 decade by using a neural network retrieval algorithm.
Statistical analysis of the seasonal variation in the twinning rate.
Fellman, J; Eriksson, A W
1999-03-01
There have been few secular analyses of the seasonal variation in human twinning and the results are conflicting. One reason for this is that the seasonal pattern of twinning varies in different populations and at different periods. Another reason is that the statistical methods used are different. The changing pattern of seasonal variation in twinning rates and total maternities in Denmark was traced for three periods (1855-69, 1870-94, and 1937-84). Two alternative methods of analysis are considered. The method of Walter and Elwood and a trigonometric regression model give closely similar results. The seasonal distribution of twin maternities for the periods in the 19th century showed highly significant departures. For both twin and general maternities, the main peaks can be seen from March to June and a local peak in September. During the spring-summer season the twinning rates were higher than the total birth rates, indicating a stronger seasonal variation for the twin maternities than for the general maternities. For 1937-84, there was a similar, but less accentuated, pattern. Studies of other populations are compared with the Danish results. The more accentuated seasonal variation of twinning in the past indicate that some factors in the past affected women during summer-autumn and around Christmas time, making them more fecund and particularly to be more prone to polyovulation and/or more able to complete a gestation with multiple embryos.
Introduction to the statistical analysis of two-color microarray data.
Bremer, Martina; Himelblau, Edward; Madlung, Andreas
2010-01-01
Microarray experiments have become routine in the past few years in many fields of biology. Analysis of array hybridizations is often performed with the help of commercial software programs, which produce gene lists, graphs, and sometimes provide values for the statistical significance of the results. Exactly what is computed by many of the available programs is often not easy to reconstruct or may even be impossible to know for the end user. It is therefore not surprising that many biology students and some researchers using microarray data do not fully understand the nature of the underlying statistics used to arrive at the results.We have developed a module that we have used successfully in undergraduate biology and statistics education that allows students to get a better understanding of both the basic biological and statistical theory needed to comprehend primary microarray data. The module is intended for the undergraduate level but may be useful to anyone who is new to the field of microarray biology. Additional course material that was developed for classroom use can be found at http://www.polyploidy.org/ .In our undergraduate classrooms we encourage students to manipulate microarray data using Microsoft Excel to reinforce some of the concepts they learn. We have included instructions for some of these manipulations throughout this chapter (see the "Do this..." boxes). However, it should be noted that while Excel can effectively analyze our small sample data set, more specialized software would typically be used to analyze full microarray data sets. Nevertheless, we believe that manipulating a small data set with Excel can provide insights into the workings of more advanced analysis software. PMID:20652509
NASA Astrophysics Data System (ADS)
Allen, Kirk
The Statistics Concept Inventory (SCI) is a multiple choice test designed to assess students' conceptual understanding of topics typically encountered in an introductory statistics course. This dissertation documents the development of the SCI from Fall 2002 up to Spring 2006. The first phase of the project essentially sought to answer the question: "Can you write a test to assess topics typically encountered in introductory statistics?" Book One presents the results utilized in answering this question in the affirmative. The bulk of the results present the development and evolution of the items, primarily relying on objective metrics to gauge effectiveness but also incorporating student feedback. The second phase boils down to: "Now that you have the test, what else can you do with it?" This includes an exploration of Cronbach's alpha, the most commonly-used measure of test reliability in the literature. An online version of the SCI was designed, and its equivalency to the paper version is assessed. Adding an extra wrinkle to the online SCI, subjects rated their answer confidence. These results show a general positive trend between confidence and correct responses. However, some items buck this trend, revealing potential sources of misunderstandings, with comparisons offered to the extant statistics and probability educational research. The third phase is a re-assessment of the SCI: "Are you sure?" A factor analytic study favored a uni-dimensional structure for the SCI, although maintaining the likelihood of a deeper structure if more items can be written to tap similar topics. A shortened version of the instrument is proposed, demonstrated to be able to maintain a reliability nearly identical to that of the full instrument. Incorporating student feedback and a faculty topics survey, improvements to the items and recommendations for further research are proposed. The state of the concept inventory movement is assessed, to offer a comparison to the work presented
Bayesian Analysis of Order-Statistics Models for Ranking Data.
ERIC Educational Resources Information Center
Yu, Philip L. H.
2000-01-01
Studied the order-statistics models, extending the usual normal order-statistics model into one in which the underlying random variables followed a multivariate normal distribution. Used a Bayesian approach and the Gibbs sampling technique. Applied the proposed method to analyze presidential election data from the American Psychological…
The Higher Education System in Israel: Statistical Abstract and Analysis.
ERIC Educational Resources Information Center
Herskovic, Shlomo
This edition of a statistical abstract published every few years on the higher education system in Israel presents the most recent data available through 1990-91. The data were gathered through the cooperation of the Central Bureau of Statistics and institutions of higher education. Chapter 1 presents a summary of principal findings covering the…
A statistical analysis of icing prediction in complex terrains
NASA Astrophysics Data System (ADS)
Terborg, Amanda M.
The issue of icing has been around for decades in aviation industry, and while notable improvements have been made in the study of the formation and process of icing, the prediction of icing events is a challenge that has yet to be completely overcome. Low level icing prediction, particularly in complex terrain, has been bumped to the back burner in an attempt to perfect the models created for in-flight icing. However, over the years there have been a number of different, non-model methods used to better refine the variable involved in low-level icing prediction. One of those methods comes through statistical analysis and modeling, particularly through the use of the Classification and Regression Tree (CART) techniques. These techniques examine the statistical significance of each predictor within a data set to determine various decision rules. Those rules in which the overall misclassification error is the smallest are then used to construct a decision tree and can be used to create a forecast for icing events. Using adiabatically adjusted Rapid Update Cycle (RUC) interpolated sounding data these CART techniques are used in this study to examine icing events in the White Mountains of New Hampshire, specifically on the summit of Mount Washington. The Mount Washington Observatory (MWO), which sits on the summit and is manned year around by weather observers, is no stranger to icing occurrences. In fact, the summit sees icing events from October all the way until April, and occasionally even into May. In this study, these events are examined in detail for the October 2010 to April 2011 season, and five CART models generated for icing in general, rime icing, and glaze icing in attempt to create a decision tree or trees with a high predictive accuracy. Also examined in this study for the October 2010 to April 2011 icing season is the Air Weather Service Pamphlet (AWSP) algorithm, a decision tree model currently in use by the Air Force to predict icing events. Producing
ERIC Educational Resources Information Center
Touchton, Michael
2015-01-01
I administer a quasi-experiment using undergraduate political science majors in statistics classes to evaluate whether "flipping the classroom" (the treatment) alters students' applied problem-solving performance and satisfaction relative to students in a traditional classroom environment (the control). I also assess whether general…
Combined statistical analysis of landslide release and propagation
NASA Astrophysics Data System (ADS)
Mergili, Martin; Rohmaneo, Mohammad; Chu, Hone-Jay
2016-04-01
Statistical methods - often coupled with stochastic concepts - are commonly employed to relate areas affected by landslides with environmental layers, and to estimate spatial landslide probabilities by applying these relationships. However, such methods only concern the release of landslides, disregarding their motion. Conceptual models for mass flow routing are used for estimating landslide travel distances and possible impact areas. Automated approaches combining release and impact probabilities are rare. The present work attempts to fill this gap by a fully automated procedure combining statistical and stochastic elements, building on the open source GRASS GIS software: (1) The landslide inventory is subset into release and deposition zones. (2) We employ a traditional statistical approach to estimate the spatial release probability of landslides. (3) We back-calculate the probability distribution of the angle of reach of the observed landslides, employing the software tool r.randomwalk. One set of random walks is routed downslope from each pixel defined as release area. Each random walk stops when leaving the observed impact area of the landslide. (4) The cumulative probability function (cdf) derived in (3) is used as input to route a set of random walks downslope from each pixel in the study area through the DEM, assigning the probability gained from the cdf to each pixel along the path (impact probability). The impact probability of a pixel is defined as the average impact probability of all sets of random walks impacting a pixel. Further, the average release probabilities of the release pixels of all sets of random walks impacting a given pixel are stored along with the area of the possible release zone. (5) We compute the zonal release probability by increasing the release probability according to the size of the release zone - the larger the zone, the larger the probability that a landslide will originate from at least one pixel within this zone. We
Parallelization of the Physical-Space Statistical Analysis System (PSAS)
NASA Technical Reports Server (NTRS)
Larson, J. W.; Guo, J.; Lyster, P. M.
1999-01-01
Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational
Advanced Materials and Solids Analysis Research Core (AMSARC)
The Advanced Materials and Solids Analysis Research Core (AMSARC), centered at the U.S. Environmental Protection Agency's (EPA) Andrew W. Breidenbach Environmental Research Center in Cincinnati, Ohio, is the foundation for the Agency's solids and surfaces analysis capabilities. ...
Advanced probabilistic risk analysis using RAVEN and RELAP-7
Rabiti, Cristian; Alfonsi, Andrea; Mandelli, Diego; Cogliati, Joshua; Kinoshita, Robert
2014-06-01
RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [1], is advancing its capability to perform statistical analyses of stochastic dynamic systems. This is aligned with its mission to provide the tools needed by the Risk Informed Safety Margin Characterization (RISMC) path-lead [2] under the Department Of Energy (DOE) Light Water Reactor Sustainability program [3]. In particular this task is focused on the synergetic development with the RELAP-7 [4] code to advance the state of the art on the safety analysis of nuclear power plants (NPP). The investigation of the probabilistic evolution of accident scenarios for a complex system such as a nuclear power plant is not a trivial challenge. The complexity of the system to be modeled leads to demanding computational requirements even to simulate one of the many possible evolutions of an accident scenario (tens of CPU/hour). At the same time, the probabilistic analysis requires thousands of runs to investigate outcomes characterized by low probability and severe consequence (tail problem). The milestone reported in June of 2013 [5] described the capability of RAVEN to implement complex control logic and provide an adequate support for the exploration of the probabilistic space using a Monte Carlo sampling strategy. Unfortunately the Monte Carlo approach is ineffective with a problem of this complexity. In the following year of development, the RAVEN code has been extended with more sophisticated sampling strategies (grids, Latin Hypercube, and adaptive sampling). This milestone report illustrates the effectiveness of those methodologies in performing the assessment of the probability of core damage following the onset of a Station Black Out (SBO) situation in a boiling water reactor (BWR). The first part of the report provides an overview of the available probabilistic analysis capabilities, ranging from the different types of distributions available, possible sampling
Thermal hydraulic limits analysis using statistical propagation of parametric uncertainties
Chiang, K. Y.; Hu, L. W.; Forget, B.
2012-07-01
The MIT Research Reactor (MITR) is evaluating the conversion from highly enriched uranium (HEU) to low enrichment uranium (LEU) fuel. In addition to the fuel element re-design, a reactor power upgraded from 6 MW to 7 MW is proposed in order to maintain the same reactor performance of the HEU core. Previous approach in analyzing the impact of engineering uncertainties on thermal hydraulic limits via the use of engineering hot channel factors (EHCFs) was unable to explicitly quantify the uncertainty and confidence level in reactor parameters. The objective of this study is to develop a methodology for MITR thermal hydraulic limits analysis by statistically combining engineering uncertainties with an aim to eliminate unnecessary conservatism inherent in traditional analyses. This method was employed to analyze the Limiting Safety System Settings (LSSS) for the MITR, which is the avoidance of the onset of nucleate boiling (ONB). Key parameters, such as coolant channel tolerances and heat transfer coefficients, were considered as normal distributions using Oracle Crystal Ball to calculate ONB. The LSSS power is determined with 99.7% confidence level. The LSSS power calculated using this new methodology is 9.1 MW, based on core outlet coolant temperature of 60 deg. C, and primary coolant flow rate of 1800 gpm, compared to 8.3 MW obtained from the analytical method using the EHCFs with same operating conditions. The same methodology was also used to calculate the safety limit (SL) for the MITR, conservatively determined using onset of flow instability (OFI) as the criterion, to verify that adequate safety margin exists between LSSS and SL. The calculated SL is 10.6 MW, which is 1.5 MW higher than LSSS. (authors)
3D statistical failure analysis of monolithic dental ceramic crowns.
Nasrin, Sadia; Katsube, Noriko; Seghi, Robert R; Rokhlin, Stanislav I
2016-07-01
For adhesively retained ceramic crown of various types, it has been clinically observed that the most catastrophic failures initiate from the cement interface as a result of radial crack formation as opposed to Hertzian contact stresses originating on the occlusal surface. In this work, a 3D failure prognosis model is developed for interface initiated failures of monolithic ceramic crowns. The surface flaw distribution parameters determined by biaxial flexural tests on ceramic plates and point-to-point variations of multi-axial stress state at the intaglio surface are obtained by finite element stress analysis. They are combined on the basis of fracture mechanics based statistical failure probability model to predict failure probability of a monolithic crown subjected to single-cycle indentation load. The proposed method is verified by prior 2D axisymmetric model and experimental data. Under conditions where the crowns are completely bonded to the tooth substrate, both high flexural stress and high interfacial shear stress are shown to occur in the wall region where the crown thickness is relatively thin while high interfacial normal tensile stress distribution is observed at the margin region. Significant impact of reduced cement modulus on these stress states is shown. While the analyses are limited to single-cycle load-to-failure tests, high interfacial normal tensile stress or high interfacial shear stress may contribute to degradation of the cement bond between ceramic and dentin. In addition, the crown failure probability is shown to be controlled by high flexural stress concentrations over a small area, and the proposed method might be of some value to detect initial crown design errors. PMID:27215334
Statistical analysis of simple repeats in the human genome
NASA Astrophysics Data System (ADS)
Piazza, F.; Liò, P.
2005-03-01
The human genome contains repetitive DNA at different level of sequence length, number and dispersion. Highly repetitive DNA is particularly rich in homo- and di-nucleotide repeats, while middle repetitive DNA is rich of families of interspersed, mobile elements hundreds of base pairs (bp) long, among which belong the Alu families. A link between homo- and di-polymeric tracts and mobile elements has been recently highlighted. In particular, the mobility of Alu repeats, which form 10% of the human genome, has been correlated with the length of poly(A) tracts located at one end of the Alu. These tracts have a rigid and non-bendable structure and have an inhibitory effect on nucleosomes, which normally compact the DNA. We performed a statistical analysis of the genome-wide distribution of lengths and inter-tract separations of poly(X) and poly(XY) tracts in the human genome. Our study shows that in humans the length distributions of these sequences reflect the dynamics of their expansion and DNA replication. By means of general tools from linguistics, we show that the latter play the role of highly-significant content-bearing terms in the DNA text. Furthermore, we find that such tracts are positioned in a non-random fashion, with an apparent periodicity of 150 bases. This allows us to extend the link between repetitive, highly mobile elements such as Alus and low-complexity words in human DNA. More precisely, we show that Alus are sources of poly(X) tracts, which in turn affect in a subtle way the combination and diversification of gene expression and the fixation of multigene families.
SUBMILLIMETER NUMBER COUNTS FROM STATISTICAL ANALYSIS OF BLAST MAPS
Patanchon, Guillaume; Ade, Peter A. R.; Griffin, Matthew; Hargrave, Peter C.; Mauskopf, Philip; Moncelsi, Lorenzo; Pascale, Enzo; Bock, James J.; Chapin, Edward L.; Halpern, Mark; Marsden, Gaelen; Scott, Douglas; Devlin, Mark J.; Dicker, Simon R.; Klein, Jeff; Rex, Marie; Gundersen, Joshua O.; Hughes, David H.; Netterfield, Calvin B.; Olmi, Luca
2009-12-20
We describe the application of a statistical method to estimate submillimeter galaxy number counts from confusion-limited observations by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Our method is based on a maximum likelihood fit to the pixel histogram, sometimes called 'P(D)', an approach which has been used before to probe faint counts, the difference being that here we advocate its use even for sources with relatively high signal-to-noise ratios. This method has an advantage over standard techniques of source extraction in providing an unbiased estimate of the counts from the bright end down to flux densities well below the confusion limit. We specifically analyze BLAST observations of a roughly 10 deg{sup 2} map centered on the Great Observatories Origins Deep Survey South field. We provide estimates of number counts at the three BLAST wavelengths 250, 350, and 500 mum; instead of counting sources in flux bins we estimate the counts at several flux density nodes connected with power laws. We observe a generally very steep slope for the counts of about -3.7 at 250 mum, and -4.5 at 350 and 500 mum, over the range approx0.02-0.5 Jy, breaking to a shallower slope below about 0.015 Jy at all three wavelengths. We also describe how to estimate the uncertainties and correlations in this method so that the results can be used for model-fitting. This method should be well suited for analysis of data from the Herschel satellite.
Bayesian Statistical Analysis of Circadian Oscillations in Fibroblasts
Cohen, Andrew L.; Leise, Tanya L.; Welsh, David K.
2012-01-01
Precise determination of a noisy biological oscillator’s period from limited experimental data can be challenging. The common practice is to calculate a single number (a point estimate) for the period of a particular time course. Uncertainty is inherent in any statistical estimator applied to noisy data, so our confidence in such point estimates depends on the quality and quantity of the data. Ideally, a period estimation method should both produce an accurate point estimate of the period and measure the uncertainty in that point estimate. A variety of period estimation methods are known, but few assess the uncertainty of the estimates, and a measure of uncertainty is rarely reported in the experimental literature. We compare the accuracy of point estimates using six common methods, only one of which can also produce uncertainty measures. We then illustrate the advantages of a new Bayesian method for estimating period, which outperforms the other six methods in accuracy of point estimates for simulated data and also provides a measure of uncertainty. We apply this method to analyze circadian oscillations of gene expression in individual mouse fibroblast cells and compute the number of cells and sampling duration required to reduce the uncertainty in period estimates to a desired level. This analysis indicates that, due to the stochastic variability of noisy intracellular oscillators, achieving a narrow margin of error can require an impractically large number of cells. In addition, we use a hierarchical model to determine the distribution of intrinsic cell periods, thereby separating the variability due to stochastic gene expression within each cell from the variability in period across the population of cells. PMID:22982138
3D statistical failure analysis of monolithic dental ceramic crowns.
Nasrin, Sadia; Katsube, Noriko; Seghi, Robert R; Rokhlin, Stanislav I
2016-07-01
For adhesively retained ceramic crown of various types, it has been clinically observed that the most catastrophic failures initiate from the cement interface as a result of radial crack formation as opposed to Hertzian contact stresses originating on the occlusal surface. In this work, a 3D failure prognosis model is developed for interface initiated failures of monolithic ceramic crowns. The surface flaw distribution parameters determined by biaxial flexural tests on ceramic plates and point-to-point variations of multi-axial stress state at the intaglio surface are obtained by finite element stress analysis. They are combined on the basis of fracture mechanics based statistical failure probability model to predict failure probability of a monolithic crown subjected to single-cycle indentation load. The proposed method is verified by prior 2D axisymmetric model and experimental data. Under conditions where the crowns are completely bonded to the tooth substrate, both high flexural stress and high interfacial shear stress are shown to occur in the wall region where the crown thickness is relatively thin while high interfacial normal tensile stress distribution is observed at the margin region. Significant impact of reduced cement modulus on these stress states is shown. While the analyses are limited to single-cycle load-to-failure tests, high interfacial normal tensile stress or high interfacial shear stress may contribute to degradation of the cement bond between ceramic and dentin. In addition, the crown failure probability is shown to be controlled by high flexural stress concentrations over a small area, and the proposed method might be of some value to detect initial crown design errors.
NASA Astrophysics Data System (ADS)
Ekobo Akoa, Brice; Simeu, Emmanuel; Lebowsky, Fritz
2014-01-01
This paper proposes two novel approaches to Video Quality Assessment (VQA). Both approaches attempt to develop video evaluation techniques capable of replacing human judgment when rating video quality in subjective experiments. The underlying study consists of selecting fundamental quality metrics based on Human Visual System (HVS) models and using artificial intelligence solutions as well as advanced statistical analysis. This new combination enables suitable video quality ratings while taking as input multiple quality metrics. The first method uses a neural network based machine learning process. The second method consists in evaluating the video quality assessment using non-linear regression model. The efficiency of the proposed methods is demonstrated by comparing their results with those of existing work done on synthetic video artifacts. The results obtained by each method are compared with scores from a database resulting from subjective experiments.
Statistical Design, Models and Analysis for the Job Change Framework.
ERIC Educational Resources Information Center
Gleser, Leon Jay
1990-01-01
Proposes statistical methodology for testing Loughead and Black's "job change thermostat." Discusses choice of target population; relationship between job satisfaction and values, perceptions, and opportunities; and determinants of job change. (SK)
Analysis of statistical model properties from discrete nuclear structure data
NASA Astrophysics Data System (ADS)
Firestone, Richard B.
2012-02-01
Experimental M1, E1, and E2 photon strengths have been compiled from experimental data in the Evaluated Nuclear Structure Data File (ENSDF) and the Evaluated Gamma-ray Activation File (EGAF). Over 20,000 Weisskopf reduced transition probabilities were recovered from the ENSDF and EGAF databases. These transition strengths have been analyzed for their dependence on transition energies, initial and final level energies, spin/parity dependence, and nuclear deformation. ENSDF BE1W values were found to increase exponentially with energy, possibly consistent with the Axel-Brink hypothesis, although considerable excess strength observed for transitions between 4-8 MeV. No similar energy dependence was observed in EGAF or ARC data. BM1W average values were nearly constant at all energies above 1 MeV with substantial excess strength below 1 MeV and between 4-8 MeV. BE2W values decreased exponentially by a factor of 1000 from 0 to 16 MeV. The distribution of ENSDF transition probabilities for all multipolarities could be described by a lognormal statistical distribution. BE1W, BM1W, and BE2W strengths all increased substantially for initial transition level energies between 4-8 MeV possibly due to dominance of spin-flip and Pygmy resonance transitions at those excitations. Analysis of the average resonance capture data indicated no transition probability dependence on final level spins or energies between 0-3 MeV. The comparison of favored to unfavored transition probabilities for odd-A or odd-Z targets indicated only partial support for the expected branching intensity ratios with many unfavored transitions having nearly the same strength as favored ones. Average resonance capture BE2W transition strengths generally increased with greater deformation. Analysis of ARC data suggest that there is a large E2 admixture in M1 transitions with the mixing ratio δ ≈ 1.0. The ENSDF reduced transition strengths were considerably stronger than those derived from capture gamma ray
Application of the Statistical ICA Technique in the DANCE Data Analysis
NASA Astrophysics Data System (ADS)
Baramsai, Bayarbadrakh; Jandel, M.; Bredeweg, T. A.; Rusev, G.; Walker, C. L.; Couture, A.; Mosby, S.; Ullmann, J. L.; Dance Collaboration
2015-10-01
The Detector for Advanced Neutron Capture Experiments (DANCE) at the Los Alamos Neutron Science Center is used to improve our understanding of the neutron capture reaction. DANCE is a highly efficient 4 π γ-ray detector array consisting of 160 BaF2 crystals which make it an ideal tool for neutron capture experiments. The (n, γ) reaction Q-value equals to the sum energy of all γ-rays emitted in the de-excitation cascades from the excited capture state to the ground state. The total γ-ray energy is used to identify reactions on different isotopes as well as the background. However, it's challenging to identify contribution in the Esum spectra from different isotopes with the similar Q-values. Recently we have tested the applicability of modern statistical methods such as Independent Component Analysis (ICA) to identify and separate different (n, γ) reaction yields on different isotopes that are present in the target material. ICA is a recently developed computational tool for separating multidimensional data into statistically independent additive subcomponents. In this conference talk, we present some results of the application of ICA algorithms and its modification for the DANCE experimental data analysis. This research is supported by the U. S. Department of Energy, Office of Science, Nuclear Physics under the Early Career Award No. LANL20135009.
Statistical analysis of synaptic transmission: model discrimination and confidence limits.
Stricker, C; Redman, S; Daley, D
1994-01-01
Procedures for discriminating between competing statistical models of synaptic transmission, and for providing confidence limits on the parameters of these models, have been developed. These procedures were tested against simulated data and were used to analyze the fluctuations in synaptic currents evoked in hippocampal neurones. All models were fitted to data using the Expectation-Maximization algorithm and a maximum likelihood criterion. Competing models were evaluated using the log-likelihood ratio (Wilks statistic). When the competing models were not nested, Monte Carlo sampling of the model used as the null hypothesis (H0) provided density functions against which H0 and the alternate model (H1) were tested. The statistic for the log-likelihood ratio was determined from the fit of H0 and H1 to these probability densities. This statistic was used to determine the significance level at which H0 could be rejected for the original data. When the competing models were nested, log-likelihood ratios and the chi 2 statistic were used to determine the confidence level for rejection. Once the model that provided the best statistical fit to the data was identified, many estimates for the model parameters were calculated by resampling the original data. Bootstrap techniques were then used to obtain the confidence limits of these parameters. PMID:7948672
New advances in methodology for statistical tests useful in geostatistical studies
Borgman, L.E.
1988-05-01
Methodology for statistical procedures to perform tests of hypothesis pertaining to various aspects of geostatistical investigations has been slow in developing. The correlated nature of the data precludes most classical tests and makes the design of new tests difficult. Recent studies have led to modifications of the classical t test which allow for the intercorrelation. In addition, results for certain nonparametric tests have been obtained. The conclusions of these studies provide a variety of new tools for the geostatistician in deciding questions on significant differences and magnitudes.
{chi}{sup 2} versus median statistics in supernova type Ia data analysis
Barreira, A.; Avelino, P. P.
2011-10-15
In this paper we compare the performances of the {chi}{sup 2} and median likelihood analysis in the determination of cosmological constraints using type Ia supernovae data. We perform a statistical analysis using the 307 supernovae of the Union 2 compilation of the Supernova Cosmology Project and find that the {chi}{sup 2} statistical analysis yields tighter cosmological constraints than the median statistic if only supernovae data is taken into account. We also show that when additional measurements from the cosmic microwave background and baryonic acoustic oscillations are considered, the combined cosmological constraints are not strongly dependent on whether one applies the {chi}{sup 2} statistic or the median statistic to the supernovae data. This indicates that, when complementary information from other cosmological probes is taken into account, the performances of the {chi}{sup 2} and median statistics are very similar, demonstrating the robustness of the statistical analysis.
Interfaces between statistical analysis packages and the ESRI geographic information system
NASA Technical Reports Server (NTRS)
Masuoka, E.
1980-01-01
Interfaces between ESRI's geographic information system (GIS) data files and real valued data files written to facilitate statistical analysis and display of spatially referenced multivariable data are described. An example of data analysis which utilized the GIS and the statistical analysis system is presented to illustrate the utility of combining the analytic capability of a statistical package with the data management and display features of the GIS.
Gene Identification Algorithms Using Exploratory Statistical Analysis of Periodicity
NASA Astrophysics Data System (ADS)
Mukherjee, Shashi Bajaj; Sen, Pradip Kumar
2010-10-01
Studying periodic pattern is expected as a standard line of attack for recognizing DNA sequence in identification of gene and similar problems. But peculiarly very little significant work is done in this direction. This paper studies statistical properties of DNA sequences of complete genome using a new technique. A DNA sequence is converted to a numeric sequence using various types of mappings and standard Fourier technique is applied to study the periodicity. Distinct statistical behaviour of periodicity parameters is found in coding and non-coding sequences, which can be used to distinguish between these parts. Here DNA sequences of Drosophila melanogaster were analyzed with significant accuracy.
NASA Astrophysics Data System (ADS)
Fernández-González, Daniel; Martín-Duarte, Ramón; Ruiz-Bustinza, Íñigo; Mochón, Javier; González-Gasca, Carmen; Verdeja, Luis Felipe
2016-08-01
Blast furnace operators expect to get sinter with homogenous and regular properties (chemical and mechanical), necessary to ensure regular blast furnace operation. Blends for sintering also include several iron by-products and other wastes that are obtained in different processes inside the steelworks. Due to their source, the availability of such materials is not always consistent, but their total production should be consumed in the sintering process, to both save money and recycle wastes. The main scope of this paper is to obtain the least expensive iron ore blend for the sintering process, which will provide suitable chemical and mechanical features for the homogeneous and regular operation of the blast furnace. The systematic use of statistical tools was employed to analyze historical data, including linear and partial correlations applied to the data and fuzzy clustering based on the Sugeno Fuzzy Inference System to establish relationships among the available variables.
NASA Astrophysics Data System (ADS)
Fernández-González, Daniel; Martín-Duarte, Ramón; Ruiz-Bustinza, Íñigo; Mochón, Javier; González-Gasca, Carmen; Verdeja, Luis Felipe
2016-06-01
Blast furnace operators expect to get sinter with homogenous and regular properties (chemical and mechanical), necessary to ensure regular blast furnace operation. Blends for sintering also include several iron by-products and other wastes that are obtained in different processes inside the steelworks. Due to their source, the availability of such materials is not always consistent, but their total production should be consumed in the sintering process, to both save money and recycle wastes. The main scope of this paper is to obtain the least expensive iron ore blend for the sintering process, which will provide suitable chemical and mechanical features for the homogeneous and regular operation of the blast furnace. The systematic use of statistical tools was employed to analyze historical data, including linear and partial correlations applied to the data and fuzzy clustering based on the Sugeno Fuzzy Inference System to establish relationships among the available variables.
Radar Derived Spatial Statistics of Summer Rain. Volume 2; Data Reduction and Analysis
NASA Technical Reports Server (NTRS)
Konrad, T. G.; Kropfli, R. A.
1975-01-01
Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.
NASA Astrophysics Data System (ADS)
McCray, Wilmon Wil L., Jr.
The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization
Statistical Power Analysis in Education Research. NCSER 2010-3006
ERIC Educational Resources Information Center
Hedges, Larry V.; Rhoads, Christopher
2010-01-01
This paper provides a guide to calculating statistical power for the complex multilevel designs that are used in most field studies in education research. For multilevel evaluation studies in the field of education, it is important to account for the impact of clustering on the standard errors of estimates of treatment effects. Using ideas from…
Statistical models and NMR analysis of polymer microstructure
Technology Transfer Automated Retrieval System (TEKTRAN)
Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...
Did Tanzania Achieve the Second Millennium Development Goal? Statistical Analysis
ERIC Educational Resources Information Center
Magoti, Edwin
2016-01-01
Development Goal "Achieve universal primary education", the challenges faced, along with the way forward towards achieving the fourth Sustainable Development Goal "Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all". Statistics show that Tanzania has made very promising steps…
Statistical Analysis Tools for Learning in Engineering Laboratories.
ERIC Educational Resources Information Center
Maher, Carolyn A.
1990-01-01
Described are engineering programs that have used automated data acquisition systems to implement data collection and analyze experiments. Applications include a biochemical engineering laboratory, heat transfer performance, engineering materials testing, mechanical system reliability, statistical control laboratory, thermo-fluid laboratory, and a…
Private School Universe Survey, 1991-92. Statistical Analysis Report.
ERIC Educational Resources Information Center
Broughman, Stephen; And Others
This report on the private school universe, a data collection system developed by the National Center for Education Statistics, presents data on schools with grades kindergarten through 12 by school size, school level, religious orientation, geographical region, and program emphasis. Numbers of students and teachers are reported in the same…
The PRIME System: Computer Programs for Statistical Analysis.
ERIC Educational Resources Information Center
Veldman, Donald J.
PRIME is a library of 44 batch-oriented computer routines: 20 major package programs, which use 12 statistical utility routines, and 12 other utility routines for input/output and data manipulation. This manual contains a general description of data preparation and coding, standard control cards, input deck arrangement, standard options, and…
Mazumdar, Madhu; Banerjee, Samprit; Van Epps, Heather L
2010-01-01
A majority of original articles published in biomedical journals include some form of statistical analysis. Unfortunately, many of the articles contain errors in statistical design and/or analysis. These errors are worrisome, as the misuse of statistics jeopardizes the process of scientific discovery and the accumulation of scientific knowledge. To help avoid these errors and improve statistical reporting, four approaches are suggested: (1) development of guidelines for statistical reporting that could be adopted by all journals, (2) improvement in statistics curricula in biomedical research programs with an emphasis on hands-on teaching by biostatisticians, (3) expansion and enhancement of biomedical science curricula in statistics programs, and (4) increased participation of biostatisticians in the peer review process along with the adoption of more rigorous journal editorial policies regarding statistics. In this chapter, we provide an overview of these issues with emphasis to the field of molecular biology and highlight the need for continuing efforts on all fronts.
The Tuition Advance Fund: An Analysis Prepared for Boston University.
ERIC Educational Resources Information Center
Botsford, Keith
Three models for anlayzing the Tuition Advance Fund (TAF) are examined. The three models are: projections by the Institute for Demographic and Economic Studies (IDES), projections by Data Resources, Inc. (DRI), and the Tuition Advance Fund Simulation (TAFSIM) models from Boston University. Analysis of the TAF is based on enrollment, price, and…
Research on the integrative strategy of spatial statistical analysis of GIS
NASA Astrophysics Data System (ADS)
Xie, Zhong; Han, Qi Juan; Wu, Liang
2008-12-01
Presently, the spacial social and natural phenomenon is studied by both the GIS technique and statistics methods. However, plenty of complex practical applications restrict these research methods. The data models and technologies exploited are full of special localization. This paper firstly sums up the requirement of spacial statistical analysis. On the base of the requirement, the universal spatial statistical models are transformed into the function tools in statistical GIS system. A pyramidal structure of three layers is brought forward. Therefore, it is feasible to combine the techniques of spacial dada management, searches and visualization in GIS with the methods of processing data in the statistic analysis. It will form an integrative statistical GIS environment with the management, analysis, application and assistant decision-making of spacial statistical information.
NASA Astrophysics Data System (ADS)
Murari, A.; Gelfusa, M.; Peluso, E.; Gaudio, P.; Mazon, D.; Hawkes, N.; Point, G.; Alper, B.; Eich, T.
2014-12-01
In a Tokamak the configuration of the magnetic fields remains the key element to improve performance and to maximise the scientific exploitation of the device. On the other hand, the quality of the reconstructed fields depends crucially on the measurements available. Traditionally in the least square minimisation phase of the algorithms, used to obtain the magnetic field topology, all the diagnostics are given the same weights, a part from a corrective factor taking into account the error bars. This assumption unduly penalises complex diagnostics, such as polarimetry, which have a limited number of highly significant measurements. A completely new method to choose the weights, to be given to the internal measurements of the magnetic fields for improved equilibrium reconstructions, is presented in this paper. The approach is based on various statistical indicators applied to the residuals, the difference between the actual measurements and their estimates from the reconstructed equilibrium. The potential of the method is exemplified using the measurements of the Faraday rotation derived from JET polarimeter. The results indicate quite clearly that the weights have to be determined carefully, since the inappropriate choice can have significant repercussions on the quality of the magnetic reconstruction both in the edge and in the core. These results confirm the limitations of the assumption that all the diagnostics have to be given the same weight, irrespective of the number of measurements they provide and the region of the plasma they probe.
A Statistical Framework for the Functional Analysis of Metagenomes
Sharon, Itai; Pati, Amrita; Markowitz, Victor; Pinter, Ron Y.
2008-10-01
Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.
Statistical Analysis of CFD Solutions from the Drag Prediction Workshop
NASA Technical Reports Server (NTRS)
Hemsch, Michael J.
2002-01-01
A simple, graphical framework is presented for robust statistical evaluation of results obtained from N-Version testing of a series of RANS CFD codes. The solutions were obtained by a variety of code developers and users for the June 2001 Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration used for the computational tests is the DLR-F4 wing-body combination previously tested in several European wind tunnels and for which a previous N-Version test had been conducted. The statistical framework is used to evaluate code results for (1) a single cruise design point, (2) drag polars and (3) drag rise. The paper concludes with a discussion of the meaning of the results, especially with respect to predictability, Validation, and reporting of solutions.
Statistical Methods for Rapid Aerothermal Analysis and Design Technology
NASA Technical Reports Server (NTRS)
Morgan, Carolyn; DePriest, Douglas; Thompson, Richard (Technical Monitor)
2002-01-01
The cost and safety goals for NASA's next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to establish statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The research work was focused on establishing the suitable mathematical/statistical models for these purposes. It is anticipated that the resulting models can be incorporated into a software tool to provide rapid, variable-fidelity, aerothermal environments to predict heating along an arbitrary trajectory. This work will support development of an integrated design tool to perform automated thermal protection system (TPS) sizing and material selection.
Common misconceptions about data analysis and statistics1
Motulsky, Harvey J
2015-01-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: (1) P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. (2) Overemphasis on P values rather than on the actual size of the observed effect. (3) Overuse of statistical hypothesis testing, and being seduced by the word “significant”. (4) Overreliance on standard errors, which are often misunderstood. PMID:25692012
Statistical analysis of motion contrast in optical coherence tomography angiography
NASA Astrophysics Data System (ADS)
Cheng, Yuxuan; Guo, Li; Pan, Cong; Lu, Tongtong; Hong, Tianyu; Ding, Zhihua; Li, Peng
2015-11-01
Optical coherence tomography angiography (Angio-OCT), mainly based on the temporal dynamics of OCT scattering signals, has found a range of potential applications in clinical and scientific research. Based on the model of random phasor sums, temporal statistics of the complex-valued OCT signals are mathematically described. Statistical distributions of the amplitude differential and complex differential Angio-OCT signals are derived. The theories are validated through the flow phantom and live animal experiments. Using the model developed, the origin of the motion contrast in Angio-OCT is mathematically explained, and the implications in the improvement of motion contrast are further discussed, including threshold determination and its residual classification error, averaging method, and scanning protocol. The proposed mathematical model of Angio-OCT signals can aid in the optimal design of the system and associated algorithms.
Statistical analysis of modeling error in structural dynamic systems
NASA Technical Reports Server (NTRS)
Hasselman, T. K.; Chrostowski, J. D.
1990-01-01
The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.
Ambiguity and nonidentifiability in the statistical analysis of neural codes
Amarasingham, Asohan; Geman, Stuart; Harrison, Matthew T.
2015-01-01
Many experimental studies of neural coding rely on a statistical interpretation of the theoretical notion of the rate at which a neuron fires spikes. For example, neuroscientists often ask, “Does a population of neurons exhibit more synchronous spiking than one would expect from the covariability of their instantaneous firing rates?” For another example, “How much of a neuron’s observed spiking variability is caused by the variability of its instantaneous firing rate, and how much is caused by spike timing variability?” However, a neuron’s theoretical firing rate is not necessarily well-defined. Consequently, neuroscientific questions involving the theoretical firing rate do not have a meaning in isolation but can only be interpreted in light of additional statistical modeling choices. Ignoring this ambiguity can lead to inconsistent reasoning or wayward conclusions. We illustrate these issues with examples drawn from the neural-coding literature. PMID:25934918
Computational and Statistical Analysis of Protein Mass Spectrometry Data
Noble, William Stafford; MacCoss, Michael J.
2012-01-01
High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve. PMID:22291580
Advanced Fingerprint Analysis Project Fingerprint Constituents
GM Mong; CE Petersen; TRW Clauss
1999-10-29
The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.
Advanced nuclear rocket engine mission analysis
Ramsthaler, J.; Farbman, G.; Sulmeisters, T.; Buden, D.; Harris, P.
1987-12-01
The use of a derivative of the NERVA engine developed from 1955 to 1973 was evluated for potential application to Air Force orbital transfer and maneuvering missions in the time period 1995 to 2020. The NERVA stge was found to have lower life cycle costs (LCC) than an advanced chemical stage for performing low earth orbit (LEO) to geosynchronous orbit (GEO0 missions at any level of activity greater than three missions per year. It had lower life cycle costs than a high performance nuclear electric engine at any level of LEO to GEO mission activity. An examination of all unmanned orbital transfer and maneuvering missions from the Space Transportation Architecture study (STAS 111-3) indicated a LCC advantage for the NERVA stage over the advanced chemical stage of fifteen million dollars. The cost advanced accured from both the orbital transfer and maneuvering missions. Parametric analyses showed that the specific impulse of the NERVA stage and the cost of delivering material to low earth orbit were the most significant factors in the LCC advantage over the chemical stage. Lower development costs and a higher thrust gave the NERVA engine an LCC advantage over the nuclear electric stage. An examination of technical data from the Rover/NERVA program indicated that development of the NERVA stage has a low technical risk, and the potential for high reliability and safe operation. The data indicated the NERVA engine had a great flexibility which would permit a single stage to perform all Air Force missions.
Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review
NASA Technical Reports Server (NTRS)
Antonsson, Erik; Gombosi, Tamas
2005-01-01
Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.
Abut, Fatih; Akay, Mehmet Fatih
2015-01-01
Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance. PMID:26346869
Abut, Fatih; Akay, Mehmet Fatih
2015-01-01
Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-05-05
... HUMAN SERVICES Food and Drug Administration Guidance for Industry on Documenting Statistical Analysis...: The Food and Drug Administration (FDA) is announcing the availability of a guidance for industry 197 entitled ``Documenting Statistical Analysis Programs and Data Files.'' This guidance is provided to...
Statistics Education Research in Malaysia and the Philippines: A Comparative Analysis
ERIC Educational Resources Information Center
Reston, Enriqueta; Krishnan, Saras; Idris, Noraini
2014-01-01
This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000-2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed…
Cost-effectiveness analysis: a proposal of new reporting standards in statistical analysis.
Bang, Heejung; Zhao, Hongwei
2014-01-01
Cost-effectiveness analysis (CEA) is a method for evaluating the outcomes and costs of competing strategies designed to improve health, and has been applied to a variety of different scientific fields. Yet there are inherent complexities in cost estimation and CEA from statistical perspectives (e.g., skewness, bidimensionality, and censoring). The incremental cost-effectiveness ratio that represents the additional cost per unit of outcome gained by a new strategy has served as the most widely accepted methodology in the CEA. In this article, we call for expanded perspectives and reporting standards reflecting a more comprehensive analysis that can elucidate different aspects of available data. Specifically, we propose that mean- and median-based incremental cost-effectiveness ratios and average cost-effectiveness ratios be reported together, along with relevant summary and inferential statistics, as complementary measures for informed decision making.
Statistical analysis of wing/fin buffeting response
NASA Astrophysics Data System (ADS)
Lee, B. H. K.
2002-05-01
The random nature of the aerodynamic loading on the wing and tail structures of an aircraft makes it necessary to adopt a statistical approach in the prediction of the buffeting response. This review describes a buffeting prediction technique based on rigid model pressure measurements that is commonly used in North America, and also the buffet excitation parameter technique favored by many researchers in the UK. It is shown that the two models are equivalent and have their origin based on a statistical theory of the response of a mechanical system to a random load. In formulating the model for predicting aircraft response at flight conditions using rigid model wind tunnel pressure measurements, the wing (fin) is divided into panels, and the load is computed from measured pressure fluctuations at the center of each panel. The methods used to model pressure correlation between panels are discussed. The coupling between the wing (fin) motion and the induced aerodynamics using a doublet-lattice unsteady aerodynamics code is described. The buffet excitation parameter approach to predict flight test response using wind tunnel model data is derived from the equations for the pressure model formulation. Examples of flight correlation with prediction based on wind tunnel measurements for wing and vertical tail buffeting response are presented for a number of aircraft. For rapid maneuvers inside the buffet regime, the statistical properties of the buffet load are usually non-stationary because of the short time records and difficulties in maintaining constant flight conditions. The time history of the applied load is segmented into a number of time intervals. In each time segment, the non-stationary load is represented as a product of a deterministic shaping function and a random function. Various forms of the load power spectral density that permits analytical solution of the mean square displacement and acceleration response are considered. Illustrations are given using F
Statistical analysis of epidemiologic data of pregnancy outcomes
Butler, W.J.; Kalasinski, L.A. )
1989-02-01
In this paper, a generalized logistic regression model for correlated observations is used to analyze epidemiologic data on the frequency of spontaneous abortion among a group of women office workers. The results are compared to those obtained from the use of the standard logistic regression model that assumes statistical independence among all the pregnancies contributed by one woman. In this example, the correlation among pregnancies from the same woman is fairly small and did not have a substantial impact on the magnitude of estimates of parameters of the model. This is due at least partly to the small average number of pregnancies contributed by each woman.
Statistical Analysis of Noisy Signals Using Classification Tools
Thompson, Sandra E.; Heredia-Langner, Alejandro; Johnson, Timothy J.; Foster, Nancy S.; Valentine, Nancy B.; Amonette, James E.
2005-06-04
The potential use of chemicals, biotoxins and biological pathogens are a threat to military and police forces as well as the general public. Rapid identification of these agents is made difficult due to the noisy nature of the signal that can be obtained from portable, in-field sensors. In previously published articles, we created a flowchart that illustrated a method for triaging bacterial identification by combining standard statistical techniques for discrimination and identification with mid-infrared spectroscopic data. The present work documents the process of characterizing and eliminating the sources of the noise and outlines how multidisciplinary teams are necessary to accomplish that goal.
Period04: Statistical analysis of large astronomical time series
NASA Astrophysics Data System (ADS)
Lenz, Patrick; Breger, Michel
2014-07-01
Period04 statistically analyzes large astronomical time series containing gaps. It calculates formal uncertainties, can extract the individual frequencies from the multiperiodic content of time series, and provides a flexible interface to perform multiple-frequency fits with a combination of least-squares fitting and the discrete Fourier transform algorithm. Period04, written in Java/C++, supports the SAMP communication protocol to provide interoperability with other applications of the Virtual Observatory. It is a reworked and extended version of Period98 (Sperl 1998) and PERIOD/PERDET (Breger 1990).
Statistical analysis of multivariate atmospheric variables. [cloud cover
NASA Technical Reports Server (NTRS)
Tubbs, J. D.
1979-01-01
Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.
ROOT: A C++ framework for petabyte data storage, statistical analysis and visualization
Antcheva, I.; Ballintijn, M.; Bellenot, B.; Biskup, M.; Brun, R.; Buncic, N.; Canal, Ph.; Casadei, D.; Couet, O.; Fine, V.; Franco, L.; /CERN /CERN
2009-01-01
ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, the RooFit package allows the user to perform complex data modeling and fitting while the RooStats library provides abstractions and implementations for advanced statistical tools. Multivariate classification methods based on machine learning techniques are available via the TMVA package. A central piece in these analysis tools are the histogram classes which provide binning of one- and multi-dimensional data. Results can be saved in high-quality graphical formats like Postscript and PDF or in bitmap formats like JPG or GIF. The result can also be stored into ROOT macros that allow a full recreation and rework of the graphics. Users typically create their analysis macros step by step, making use of the interactive C++ interpreter CINT, while running over small data samples. Once the development is finished, they can run these macros at full compiled speed over large data sets, using on-the-fly compilation, or by creating a stand-alone batch program. Finally, if processing farms are available, the user can reduce the execution time of intrinsically parallel tasks - e.g. data mining in HEP - by using PROOF, which will take care of optimally
Arciuli, Joanne; Torkildsen, Janne von Koss
2012-01-01
Mastery of language can be a struggle for some children. Amongst those that succeed in achieving this feat there is variability in proficiency. Cognitive scientists remain intrigued by this variation. A now substantial body of research suggests that language acquisition is underpinned by a child’s capacity for statistical learning (SL). Moreover, a growing body of research has demonstrated that variability in SL is associated with variability in language proficiency. Yet, there is a striking lack of longitudinal data. To date, there has been no comprehensive investigation of whether a capacity for SL in young children is, in fact, associated with language proficiency in subsequent years. Here we review key studies that have led to the need for this longitudinal research. Advancing the language acquisition debate via longitudinal research has the potential to transform our understanding of typical development as well as disorders such as autism, specific language impairment, and dyslexia. PMID:22969746
Arciuli, Joanne; Torkildsen, Janne von Koss
2012-01-01
Mastery of language can be a struggle for some children. Amongst those that succeed in achieving this feat there is variability in proficiency. Cognitive scientists remain intrigued by this variation. A now substantial body of research suggests that language acquisition is underpinned by a child's capacity for statistical learning (SL). Moreover, a growing body of research has demonstrated that variability in SL is associated with variability in language proficiency. Yet, there is a striking lack of longitudinal data. To date, there has been no comprehensive investigation of whether a capacity for SL in young children is, in fact, associated with language proficiency in subsequent years. Here we review key studies that have led to the need for this longitudinal research. Advancing the language acquisition debate via longitudinal research has the potential to transform our understanding of typical development as well as disorders such as autism, specific language impairment, and dyslexia.
Advanced tracking systems design and analysis
NASA Technical Reports Server (NTRS)
Potash, R.; Floyd, L.; Jacobsen, A.; Cunningham, K.; Kapoor, A.; Kwadrat, C.; Radel, J.; Mccarthy, J.
1989-01-01
The results of an assessment of several types of high-accuracy tracking systems proposed to track the spacecraft in the National Aeronautics and Space Administration (NASA) Advanced Tracking and Data Relay Satellite System (ATDRSS) are summarized. Tracking systems based on the use of interferometry and ranging are investigated. For each system, the top-level system design and operations concept are provided. A comparative system assessment is presented in terms of orbit determination performance, ATDRSS impacts, life-cycle cost, and technological risk.
Advanced surface design for logistics analysis
NASA Astrophysics Data System (ADS)
Brown, Tim R.; Hansen, Scott D.
The development of anthropometric arm/hand and tool models and their manipulation in a large system model for maintenance simulation are discussed. The use of Advanced Surface Design and s-fig technology in anthropometrics, and three-dimensional graphics simulation tools, are found to achieve a good balance between model manipulation speed and model accuracy. The present second generation models are shown to be twice as fast to manipulate as the first generation b-surf models, to be easier to manipulate into various configurations, and to more closely approximate human contours.
[Statistical analysis of fabrication of indirect single restorations].
Sato, T; Kawawa, A; Okada, D; Ohno, S; Akiba, H; Watanabe, Y; Endo, K; Mayanagi, A; Miura, H; Hasegawa, S
1999-09-01
A statistical survey based on laboratory records was performed on the number of indirect restorations fabricated at the dental hospital of Tokyo Medical and Dental University from April 1 to September 30, 1997. A comparison was also carried out with a previous survey, which had been carried out in 1986, in order to detect any change and possible alterations in the near future. Based on the results of this statistical survey, the conclusions were as follows: 1. A total of 9,126 indirect restorations were fabricated during the six month period in 1997; among them, 8,007 (87.7%) restorations were covered by health insurance and 1,119 (12.3%) restorations were not. 2. The most common restoration was the cast post and core (28.6%), followed by full crowns (18.5%) and removable partial dentures (15.6%). On the other hand, the least number were post crowns (0.03%) and resin jacket crowns (0.2%). 3. When making a comparison with the data in 1986, an increase in the number of removable partial dentures and a decrease in the number of inlays were the most distinctive features. 4. For anterior teeth, resin-veneered crowns were most common, especially for lower teeth. The percentage of restorations, which were not covered by health insurance, decreased from 45.0% (in 1986) to 12.3% (in 1997).
Statistical analysis of bankrupting and non-bankrupting stocks
NASA Astrophysics Data System (ADS)
Li, Qian; Wang, Fengzhong; Wei, Jianrong; Liang, Yuan; Huang, Jiping; Stanley, H. Eugene
2012-04-01
The recent financial crisis has caused extensive world-wide economic damage, affecting in particular those who invested in companies that eventually filed for bankruptcy. A better understanding of stocks that become bankrupt would be helpful in reducing risk in future investments. Economists have conducted extensive research on this topic, and here we ask whether statistical physics concepts and approaches may offer insights into pre-bankruptcy stock behavior. To this end, we study all 20092 stocks listed in US stock markets for the 20-year period 1989-2008, including 4223 (21 percent) that became bankrupt during that period. We find that, surprisingly, the distributions of the daily returns of those stocks that become bankrupt differ significantly from those that do not. Moreover, these differences are consistent for the entire period studied. We further study the relation between the distribution of returns and the length of time until bankruptcy, and observe that larger differences of the distribution of returns correlate with shorter time periods preceding bankruptcy. This behavior suggests that sharper fluctuations in the stock price occur when the stock is closer to bankruptcy. We also analyze the cross-correlations between the return and the trading volume, and find that stocks approaching bankruptcy tend to have larger return-volume cross-correlations than stocks that are not. Furthermore, the difference increases as bankruptcy approaches. We conclude that before a firm becomes bankrupt its stock exhibits unusual behavior that is statistically quantifiable.
Statistical analysis of biotissues Mueller matrix images in cancer diagnostics
NASA Astrophysics Data System (ADS)
Yermolenko, Sergey; Ivashko, Pavlo; Goudail, François; Gruia, Ion
2010-11-01
This work is directed to the investigation of the scope of the technique of laser polarimetry and polarization spectrometry of oncological changes of the human prostate tissue under the conditions of multiple scattering. It was shown that the third statistic moment in the intensity distribution proved to be the most sensitive to pathological changes in orientation structure. Its value in the intensity distribution of polarization image I (0 - 90) of oncologically changed tissue is 21 times higher if compared with the similar statistic parameter of the intensity distribution of the healthy tissue. The results of studies of size linear dichroism prostate gland, as healthy and affected by malignant tumor at different stages of its development was presented. Significant difference in the values of linear dichroism and its spectral dependence in the spectral range λ = 280 - 840 nm as between research facilities, and between biotissues - healthy (or affected by benign tumors) and cancer patients was shown. These results may have diagnostic value for detection and assessment of the development of cancer.
Texture analysis with statistical methods for wheat ear extraction
NASA Astrophysics Data System (ADS)
Bakhouche, M.; Cointault, F.; Gouton, P.
2007-01-01
In agronomic domain, the simplification of crop counting, necessary for yield prediction and agronomic studies, is an important project for technical institutes such as Arvalis. Although the main objective of our global project is to conceive a mobile robot for natural image acquisition directly in a field, Arvalis has proposed us first to detect by image processing the number of wheat ears in images before to count them, which will allow to obtain the first component of the yield. In this paper we compare different texture image segmentation techniques based on feature extraction by first and higher order statistical methods which have been applied on our images. The extracted features are used for unsupervised pixel classification to obtain the different classes in the image. So, the K-means algorithm is implemented before the choice of a threshold to highlight the ears. Three methods have been tested in this feasibility study with very average error of 6%. Although the evaluation of the quality of the detection is visually done, automatic evaluation algorithms are currently implementing. Moreover, other statistical methods of higher order will be implemented in the future jointly with methods based on spatio-frequential transforms and specific filtering.
Statistical analysis of the Indus script using n-grams.
Yadav, Nisha; Joglekar, Hrishikesh; Rao, Rajesh P N; Vahia, Mayank N; Adhikari, Ronojoy; Mahadevan, Iravatham
2010-03-19
The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilization. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically n-gram Markov chains, to analyze the syntax of the Indus script. We find that unigrams follow a Zipf-Mandelbrot distribution. Text beginner and ender distributions are unequal, providing internal evidence for syntax. We see clear evidence of strong bigram correlations and extract significant pairs and triplets using a log-likelihood measure of association. Highly frequent pairs and triplets are not always highly significant. The model performance is evaluated using information-theoretic measures and cross-validation. The model can restore doubtfully read texts with an accuracy of about 75%. We find that a quadrigram Markov chain saturates information theoretic measures against a held-out corpus. Our work forms the basis for the development of a stochastic grammar which may be used to explore the syntax of the Indus script in greater detail.
How Many Studies Do You Need? A Primer on Statistical Power for Meta-Analysis
ERIC Educational Resources Information Center
Valentine, Jeffrey C.; Pigott, Therese D.; Rothstein, Hannah R.
2010-01-01
In this article, the authors outline methods for using fixed and random effects power analysis in the context of meta-analysis. Like statistical power analysis for primary studies, power analysis for meta-analysis can be done either prospectively or retrospectively and requires assumptions about parameters that are unknown. The authors provide…
Statistical analysis of loopy belief propagation in random fields
NASA Astrophysics Data System (ADS)
Yasuda, Muneki; Kataoka, Shun; Tanaka, Kazuyuki
2015-10-01
Loopy belief propagation (LBP), which is equivalent to the Bethe approximation in statistical mechanics, is a message-passing-type inference method that is widely used to analyze systems based on Markov random fields (MRFs). In this paper, we propose a message-passing-type method to analytically evaluate the quenched average of LBP in random fields by using the replica cluster variation method. The proposed analytical method is applicable to general pairwise MRFs with random fields whose distributions differ from each other and can give the quenched averages of the Bethe free energies over random fields, which are consistent with numerical results. The order of its computational cost is equivalent to that of standard LBP. In the latter part of this paper, we describe the application of the proposed method to Bayesian image restoration, in which we observed that our theoretical results are in good agreement with the numerical results for natural images.
Statistical Analysis of Complexity Generators for Cost Estimation
NASA Technical Reports Server (NTRS)
Rowell, Ginger Holmes
1999-01-01
Predicting the cost of cutting edge new technologies involved with spacecraft hardware can be quite complicated. A new feature of the NASA Air Force Cost Model (NAFCOM), called the Complexity Generator, is being developed to model the complexity factors that drive the cost of space hardware. This parametric approach is also designed to account for the differences in cost, based on factors that are unique to each system and subsystem. The cost driver categories included in this model are weight, inheritance from previous missions, technical complexity, and management factors. This paper explains the Complexity Generator framework, the statistical methods used to select the best model within this framework, and the procedures used to find the region of predictability and the prediction intervals for the cost of a mission.
Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation
NASA Technical Reports Server (NTRS)
DePriest, Douglas; Morgan, Carolyn
2003-01-01
The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.
Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities
Zayed, Nourhan; Elnemr, Heba A.
2015-01-01
The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others. PMID:26557845
Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities.
Zayed, Nourhan; Elnemr, Heba A
2015-01-01
The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others. PMID:26557845
Statistical analysis of Nomao customer votes for spots of France
NASA Astrophysics Data System (ADS)
Pálovics, Róbert; Daróczy, Bálint; Benczúr, András; Pap, Julia; Ermann, Leonardo; Phan, Samuel; Chepelianskii, Alexei D.; Shepelyansky, Dima L.
2015-08-01
We investigate the statistical properties of votes of customers for spots of France collected by the startup company Nomao. The frequencies of votes per spot and per customer are characterized by a power law distribution which remains stable on a time scale of a decade when the number of votes is varied by almost two orders of magnitude. Using the computer science methods we explore the spectrum and the eigenvalues of a matrix containing user ratings to geolocalized items. Eigenvalues nicely map to large towns and regions but show certain level of instability as we modify the interpretation of the underlying matrix. We evaluate imputation strategies that provide improved prediction performance by reaching geographically smooth eigenvectors. We point on possible links between distribution of votes and the phenomenon of self-organized criticality.
Analysis of surface sputtering on a quantum statistical basis
NASA Technical Reports Server (NTRS)
Wilhelm, H. E.
1975-01-01
Surface sputtering is explained theoretically by means of a 3-body sputtering mechanism involving the ion and two surface atoms of the solid. By means of quantum-statistical mechanics, a formula for the sputtering ratio S(E) is derived from first principles. The theoretical sputtering rate S(E) was found experimentally to be proportional to the square of the difference between incident ion energy and the threshold energy for sputtering of surface atoms at low ion energies. Extrapolation of the theoretical sputtering formula to larger ion energies indicates that S(E) reaches a saturation value and finally decreases at high ion energies. The theoretical sputtering ratios S(E) for wolfram, tantalum, and molybdenum are compared with the corresponding experimental sputtering curves in the low energy region from threshold sputtering energy to 120 eV above the respective threshold energy. Theory and experiment are shown to be in good agreement.
Power flow as a complement to statistical energy analysis and finite element analysis
NASA Technical Reports Server (NTRS)
Cuschieri, J. M.
1987-01-01
Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.
Tanavalee, Chotetawan; Luksanapruksa, Panya; Singhatanadgige, Weerasak
2016-06-01
Microsoft Excel (MS Excel) is a commonly used program for data collection and statistical analysis in biomedical research. However, this program has many limitations, including fewer functions that can be used for analysis and a limited number of total cells compared with dedicated statistical programs. MS Excel cannot complete analyses with blank cells, and cells must be selected manually for analysis. In addition, it requires multiple steps of data transformation and formulas to plot survival analysis graphs, among others. The Megastat add-on program, which will be supported by MS Excel 2016 soon, would eliminate some limitations of using statistic formulas within MS Excel.
Multivariate Statistical Analysis of MSL APXS Bulk Geochemical Data
NASA Astrophysics Data System (ADS)
Hamilton, V. E.; Edwards, C. S.; Thompson, L. M.; Schmidt, M. E.
2014-12-01
We apply cluster and factor analyses to bulk chemical data of 130 soil and rock samples measured by the Alpha Particle X-ray Spectrometer (APXS) on the Mars Science Laboratory (MSL) rover Curiosity through sol 650. Multivariate approaches such as principal components analysis (PCA), cluster analysis, and factor analysis compliment more traditional approaches (e.g., Harker diagrams), with the advantage of simultaneously examining the relationships between multiple variables for large numbers of samples. Principal components analysis has been applied with success to APXS, Pancam, and Mössbauer data from the Mars Exploration Rovers. Factor analysis and cluster analysis have been applied with success to thermal infrared (TIR) spectral data of Mars. Cluster analyses group the input data by similarity, where there are a number of different methods for defining similarity (hierarchical, density, distribution, etc.). For example, without any assumptions about the chemical contributions of surface dust, preliminary hierarchical and K-means cluster analyses clearly distinguish the physically adjacent rock targets Windjana and Stephen as being distinctly different than lithologies observed prior to Curiosity's arrival at The Kimberley. In addition, they are separated from each other, consistent with chemical trends observed in variation diagrams but without requiring assumptions about chemical relationships. We will discuss the variation in cluster analysis results as a function of clustering method and pre-processing (e.g., log transformation, correction for dust cover) and implications for interpreting chemical data. Factor analysis shares some similarities with PCA, and examines the variability among observed components of a dataset so as to reveal variations attributable to unobserved components. Factor analysis has been used to extract the TIR spectra of components that are typically observed in mixtures and only rarely in isolation; there is the potential for similar
Statistical analysis of imperfection effect on cylindrical buckling response
NASA Astrophysics Data System (ADS)
Ismail, M. S.; Purbolaksono, J.; Muhammad, N.; Andriyana, A.; Liew, H. L.
2015-12-01
It is widely reported that no efficient guidelines for modelling imperfections in composite structures are available. In response, this work evaluates the imperfection factors of axially compressed Carbon Fibre Reinforced Polymer (CFRP) cylinder with different ply angles through finite element (FE) analysis. The sensitivity of imperfection factors were analysed using design of experiment: factorial design approach. From the analysis it identified three critical factors that sensitively reacted towards buckling load. Furthermore empirical equation is proposed according to each type of cylinder. Eventually, critical buckling loads estimated by empirical equation showed good agreements with FE analysis. The design of experiment methodology is useful in identifying parameters that lead to structures imperfection tolerance.
Recent Advances in Anthocyanin Analysis and Characterization
Welch, Cara R.; Wu, Qingli; Simon, James E.
2009-01-01
Anthocyanins are a class of polyphenols responsible for the orange, red, purple and blue colors of many fruits, vegetables, grains, flowers and other plants. Consumption of anthocyanins has been linked as protective agents against many chronic diseases and possesses strong antioxidant properties leading to a variety of health benefits. In this review, we examine the advances in the chemical profiling of natural anthocyanins in plant and biological matrices using various chromatographic separations (HPLC and CE) coupled with different detection systems (UV, MS and NMR). An overview of anthocyanin chemistry, prevalence in plants, biosynthesis and metabolism, bioactivities and health properties, sample preparation and phytochemical investigations are discussed while the major focus examines the comparative advantages and disadvantages of each analytical technique. PMID:19946465
Analysis of an advanced technology subsonic turbofan incorporating revolutionary materials
NASA Technical Reports Server (NTRS)
Knip, Gerald, Jr.
1987-01-01
Successful implementation of revolutionary composite materials in an advanced turbofan offers the possibility of further improvements in engine performance and thrust-to-weight ratio relative to current metallic materials. The present analysis determines the approximate engine cycle and configuration for an early 21st century subsonic turbofan incorporating all composite materials. The advanced engine is evaluated relative to a current technology baseline engine in terms of its potential fuel savings for an intercontinental quadjet having a design range of 5500 nmi and a payload of 500 passengers. The resultant near optimum, uncooled, two-spool, advanced engine has an overall pressure ratio of 87, a bypass ratio of 18, a geared fan, and a turbine rotor inlet temperature of 3085 R. Improvements result in a 33-percent fuel saving for the specified misssion. Various advanced composite materials are used throughout the engine. For example, advanced polymer composite materials are used for the fan and the low pressure compressor (LPC).
New Statistical Approach to the Analysis of Hierarchical Data
NASA Astrophysics Data System (ADS)
Neuman, S. P.; Guadagnini, A.; Riva, M.
2014-12-01
Many variables possess a hierarchical structure reflected in how their increments vary in space and/or time. Quite commonly the increments (a) fluctuate in a highly irregular manner; (b) possess symmetric, non-Gaussian frequency distributions characterized by heavy tails that often decay with separation distance or lag; (c) exhibit nonlinear power-law scaling of sample structure functions in a midrange of lags, with breakdown in such scaling at small and large lags; (d) show extended power-law scaling (ESS) at all lags; and (e) display nonlinear scaling of power-law exponent with order of sample structure function. Some interpret this to imply that the variables are multifractal, which explains neither breakdowns in power-law scaling nor ESS. We offer an alternative interpretation consistent with all above phenomena. It views data as samples from stationary, anisotropic sub-Gaussian random fields subordinated to truncated fractional Brownian motion (tfBm) or truncated fractional Gaussian noise (tfGn). The fields are scaled Gaussian mixtures with random variances. Truncation of fBm and fGn entails filtering out components below data measurement or resolution scale and above domain scale. Our novel interpretation of the data allows us to obtain maximum likelihood estimates of all parameters characterizing the underlying truncated sub-Gaussian fields. These parameters in turn make it possible to downscale or upscale all statistical moments to situations entailing smaller or larger measurement or resolution and sampling scales, respectively. They also allow one to perform conditional or unconditional Monte Carlo simulations of random field realizations corresponding to these scales. Aspects of our approach are illustrated on field and laboratory measured porous and fractured rock permeabilities, as well as soil texture characteristics and neural network estimates of unsaturated hydraulic parameters in a deep vadose zone near Phoenix, Arizona. We also use our approach
Statistical analysis of properties of dwarf novae outbursts
NASA Astrophysics Data System (ADS)
Otulakowska-Hypka, Magdalena; Olech, Arkadiusz; Patterson, Joseph
2016-08-01
We present a statistical study of all measurable photometric features of a large sample of dwarf novae during their outbursts and superoutbursts. We used all accessible photometric data for all our objects to make the study as complete and up to date as possible. Our aim was to check correlations between these photometric features in order to constrain theoretical models which try to explain the nature of dwarf novae outbursts. We managed to confirm a few of the known correlations, that is the Stolz and Schoembs relation, the Bailey relation for long outbursts above the period gap, the relations between the cycle and supercycle lengths, amplitudes of normal and superoutbursts, amplitude and duration of superoutbursts, outburst duration and orbital period, outburst duration and mass ratio for short and normal outbursts, as well as the relation between the rise and decline rates of superoutbursts. However, we question the existence of the Kukarkin-Parenago relation but we found an analogous relation for superoutbursts. We also failed to find one presumed relation between outburst duration and mass ratio for superoutbursts. This study should help to direct theoretical work dedicated to dwarf novae.
Statistical analysis of AFE GN&C aeropass performance
NASA Technical Reports Server (NTRS)
Chang, Ho-Pen; French, Raymond A.
1990-01-01
Performance of the guidance, navigation, and control (GN&C) system used on the Aeroassist Flight Experiment (AFE) spacecraft has been studied with Monte Carlo techniques. The performance of the AFE GN&C is investigated with a 6-DOF numerical dynamic model which includes a Global Reference Atmospheric Model (GRAM) and a gravitational model with oblateness corrections. The study considers all the uncertainties due to the environment and the system itself. In the AFE's aeropass phase, perturbations on the system performance are caused by an error space which has over 20 dimensions of the correlated/uncorrelated error sources. The goal of this study is to determine, in a statistical sense, how much flight path angle error can be tolerated at entry interface (EI) and still have acceptable delta-V capability at exit to position the AFE spacecraft for recovery. Assuming there is fuel available to produce 380 ft/sec of delta-V at atmospheric exit, a 3-sigma standard deviation in flight path angle error of 0.04 degrees at EI would result in a 98-percent probability of mission success.
A statistical mechanics analysis of the set covering problem
NASA Astrophysics Data System (ADS)
Fontanari, J. F.
1996-02-01
The dependence of the optimal solution average cost 0305-4470/29/3/004/img1 of the set covering problem on the density of 1's of the incidence matrix (0305-4470/29/3/004/img2) and on the number of constraints (P) is investigated in the limit where the number of items (N) goes to infinity. The annealed approximation is employed to study two stochastic models: the constant density model, where the elements of the incidence matrix are statistically independent random variables, and the Karp model, where the rows of the incidence matrix possess the same number of 1's. Lower bounds for 0305-4470/29/3/004/img1 are presented in the case that P scales with ln N and 0305-4470/29/3/004/img2 is of order 1, as well as in the case that P scales linearly with N and 0305-4470/29/3/004/img2 is of order 1/N. It is shown that in the case that P scales with exp N and 0305-4470/29/3/004/img2 is of order 1 the annealed approximation yields exact results for both models.
Statistical analysis of dendritic spine distributions in rat hippocampal cultures
2013-01-01
Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199
Statistical analysis of the properties of foreshock density cavitons
NASA Astrophysics Data System (ADS)
Kajdič, P.; Blanco-Cano, X.; Omidi, N.; Russell, C. T.
2008-12-01
Global hybrid simulations (kinetic ions, fluid electrons) have shown the existence of foreshock density cavitons immersed in regions permeated by ULF waves (Omidi, 2007, Blanco-Cano et al., 2008). These cavitons are characterized by large depressions in magnetic field magnitude and density, and are bounded by regions with enhanced field and density. In this work we study statistical properties of foreshock cavitons observed by Cluster spacecraft between the years 2001 and 2005. We have identified approximately 90 foreshock cavitons and use magnetic field and plasma data to analyze their durations, sizes, amplitude, and orientation. We compare caviton B and n values with ambient values. We also study the foreshock conditions in which the cavitons are detected, i.e. θBV, the angle between the incoming solar wind flow and the IMF, and Mach number, among others. We also determine the characteristics of the waves that surround the cavitons or even appear within them. We find that the foreshock cavitons can be observed in various ways - some are found as single cavitons immersed in ULF waves, others appear in groups, separated temporally only by a few minutes. In some cases we find two or three cavitons that are in the process of merging into a larger structure, and still developing.
On the Statistical Analysis of X-ray Polarization Measurements
NASA Technical Reports Server (NTRS)
Strohmayer, T. E.; Kallman, T. R.
2013-01-01
In many polarimetry applications, including observations in the X-ray band, the measurement of a polarization signal can be reduced to the detection and quantification of a deviation from uniformity of a distribution of measured angles of the form alpha plus beta cosine (exp 2)(phi - phi(sub 0) (0 (is) less than phi is less than pi). We explore the statistics of such polarization measurements using both Monte Carlo simulations as well as analytic calculations based on the appropriate probability distributions. We derive relations for the number of counts required to reach a given detection level (parameterized by beta the "number of sigma's" of the measurement) appropriate for measuring the modulation amplitude alpha by itself (single interesting parameter case) or jointly with the position angle phi (two interesting parameters case). We show that for the former case when the intrinsic amplitude is equal to the well known minimum detectable polarization (MDP) it is, on average, detected at the 3sigma level. For the latter case, when one requires a joint measurement at the same confidence level, then more counts are needed, by a factor of approximately equal to 2.2, than that required to achieve the MDP level. We find that the position angle uncertainty at 1sigma confidence is well described by the relation sigma(sub pi) equals 28.5(degrees) divided by beta.
Statistical language analysis for automatic exfiltration event detection.
Robinson, David Gerald
2010-04-01
This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.
Ockham's razor and Bayesian analysis. [statistical theory for systems evaluation
NASA Technical Reports Server (NTRS)
Jefferys, William H.; Berger, James O.
1992-01-01
'Ockham's razor', the ad hoc principle enjoining the greatest possible simplicity in theoretical explanations, is presently shown to be justifiable as a consequence of Bayesian inference; Bayesian analysis can, moreover, clarify the nature of the 'simplest' hypothesis consistent with the given data. By choosing the prior probabilities of hypotheses, it becomes possible to quantify the scientific judgment that simpler hypotheses are more likely to be correct. Bayesian analysis also shows that a hypothesis with fewer adjustable parameters intrinsically possesses an enhanced posterior probability, due to the clarity of its predictions.
Peyrat, Jean-Marc; Sermesant, Maxime; Pennec, Xavier; Delingette, Hervé; Xu, Chenyang; McVeigh, Elliot R; Ayache, Nicholas
2007-11-01
We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistical analysis confirms the already established good stability of the fiber orientations and a higher variability of the laminar sheet orientations within a given species. The statistical comparison between the canine atlas and a standard human cardiac DT-MRI shows a better stability of the fiber orientations than their laminar sheet orientations between the two species. The proposed computational framework can be applied to larger databases of cardiac DT-MRIs from various species to better establish intraspecies and interspecies statistics on the anatomical structure of cardiac fibers. This information will be useful to guide the adjustment of average fiber models onto specific patients from in vivo anatomical imaging modalities.
New Test Statistics for MANOVA/Descriptive Discriminant Analysis.
ERIC Educational Resources Information Center
Coombs, William T.; Algina, James
1996-01-01
Univariate procedures proposed by M. Brown and A. Forsythe (1974) and the multivariate procedures from D. Nel and C. van der Merwe (1986) were generalized to form five new multivariate alternatives to one-way multivariate analysis of variance (MANOVA) for use when dispersion matrices are heteroscedastic. These alternatives are evaluated for Type I…
The Patterns of Teacher Compensation. Statistical Analysis Report.
ERIC Educational Resources Information Center
Chambers, Jay; Bobbitt, Sharon A.
This report presents information regarding the patterns of variation in the salaries paid to public and private school teachers in relation to various personal and job characteristics. Specifically, the analysis examines the relationship between compensation and variables such as public/private schools, gender, race/ethnic background, school level…
Using Neural Networks for Descriptive Statistical Analysis of Educational Data.
ERIC Educational Resources Information Center
Tirri, Henry; And Others
Methodological issues of using a class of neural networks called Mixture Density Networks (MDN) for discriminant analysis are discussed. MDN models have the advantage of having a rigorous probabilistic interpretation, and they have proven to be a viable alternative as a classification procedure in discrete domains. Both classification and…
Statistical analysis of unsolicited thermal sensation complaints in commercial buildings
Federspiel, C.C.
1998-10-01
Unsolicited complaints from 23,500 occupants in 690 commercial buildings were examined with regard to absolute and relative frequency of complaints, temperatures at which thermal sensation complaints (too hot or too cold) occurred, and response times and actions. The analysis shows that thermal sensation complaints are the single most common complaint of any type and that they are the overwhelming majority of environmental complaints. The analysis indicates that thermal sensation complaints are mostly the result of poor control performance and HVAC system faults rather than inter-individual differences in preferred temperatures. The analysis also shows that the neutral temperature in summer is greater than in winter, and the difference between summer and winter neutral temperatures is smaller than the difference between the midpoints of the summer and winter ASHRAE comfort zones. On average, women complain that it is cold at a higher temperature than men, and the temperature at which men complain that it is hot is more variable than for women. Analysis of response times and actions provides information that may be useful for designing a dispatching policy, and it also demonstrates that there is potential to reduce the labor cost of HVAC maintenance by 20% by reducing the frequency of thermal sensation complaints.
Granger causality--statistical analysis under a configural perspective.
von Eye, Alexander; Wiedermann, Wolfgang; Mun, Eun-Young
2014-03-01
The concept of Granger causality can be used to examine putative causal relations between two series of scores. Based on regression models, it is asked whether one series can be considered the cause for the second series. In this article, we propose extending the pool of methods available for testing hypotheses that are compatible with Granger causation by adopting a configural perspective. This perspective allows researchers to assume that effects exist for specific categories only or for specific sectors of the data space, but not for other categories or sectors. Configural Frequency Analysis (CFA) is proposed as the method of analysis from a configural perspective. CFA base models are derived for the exploratory analysis of Granger causation. These models are specified so that they parallel the regression models used for variable-oriented analysis of hypotheses of Granger causation. An example from the development of aggression in adolescence is used. The example shows that only one pattern of change in aggressive impulses over time Granger-causes change in physical aggression against peers.
Open Access Publishing Trend Analysis: Statistics beyond the Perception
ERIC Educational Resources Information Center
Poltronieri, Elisabetta; Bravo, Elena; Curti, Moreno; Maurizio Ferri,; Mancini, Cristina
2016-01-01
Introduction: The purpose of this analysis was twofold: to track the number of open access journals acquiring impact factor, and to investigate the distribution of subject categories pertaining to these journals. As a case study, journals in which the researchers of the National Institute of Health (Istituto Superiore di Sanità) in Italy have…
Statistical analysis of geodetic networks for detecting regional events
NASA Technical Reports Server (NTRS)
Granat, Robert
2004-01-01
We present an application of hidden Markov models (HMMs) to analysis of geodetic time series in Southern California. Our model fitting method uses a regularized version of the deterministic annealing expectation-maximization algorithm to ensure that model solutions are both robust and of high quality.
Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems
NASA Technical Reports Server (NTRS)
He, Yuning; Davies, Misty Dawn
2014-01-01
The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.
Modeling and analysis of advanced binary cycles
Gawlik, K.
1997-12-31
A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.
Using the statistical analysis method to assess the landslide susceptibility
NASA Astrophysics Data System (ADS)
Chan, Hsun-Chuan; Chen, Bo-An; Wen, Yo-Ting
2015-04-01
This study assessed the landslide susceptibility in Jing-Shan River upstream watershed, central Taiwan. The landslide inventories during typhoons Toraji in 2001, Mindulle in 2004, Kalmaegi and Sinlaku in 2008, Morakot in 2009, and the 0719 rainfall event in 2011, which were established by Taiwan Central Geological Survey, were used as landslide data. This study aims to assess the landslide susceptibility by using different statistical methods including logistic regression, instability index method and support vector machine (SVM). After the evaluations, the elevation, slope, slope aspect, lithology, terrain roughness, slope roughness, plan curvature, profile curvature, total curvature, average of rainfall were chosen as the landslide factors. The validity of the three established models was further examined by the receiver operating characteristic curve. The result of logistic regression showed that the factor of terrain roughness and slope roughness had a stronger impact on the susceptibility value. Instability index method showed that the factor of terrain roughness and lithology had a stronger impact on the susceptibility value. Due to the fact that the use of instability index method may lead to possible underestimation around the river side. In addition, landslide susceptibility indicated that the use of instability index method laid a potential issue about the number of factor classification. An increase of the number of factor classification may cause excessive variation coefficient of the factor. An decrease of the number of factor classification may make a large range of nearby cells classified into the same susceptibility level. Finally, using the receiver operating characteristic curve discriminate the three models. SVM is a preferred method than the others in assessment of landslide susceptibility. Moreover, SVM is further suggested to be nearly logistic regression in terms of recognizing the medium-high and high susceptibility.
An overview of the mathematical and statistical analysis component of RICIS
NASA Technical Reports Server (NTRS)
Hallum, Cecil R.
1987-01-01
Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.
Characterization of Nuclear Fuel using Multivariate Statistical Analysis
Robel, M; Robel, M; Robel, M; Kristo, M J; Kristo, M J
2007-11-27
Various combinations of reactor type and fuel composition have been characterized using principle components analysis (PCA) of the concentrations of 9 U and Pu isotopes in the 10 fuel as a function of burnup. The use of PCA allows the reduction of the 9-dimensional data (isotopic concentrations) into a 3-dimensional approximation, giving a visual representation of the changes in nuclear fuel composition with burnup. Real-world variation in the concentrations of {sup 234}U and {sup 236}U in the fresh (unirradiated) fuel was accounted for. The effects of reprocessing were also simulated. The results suggest that, 15 even after reprocessing, Pu isotopes can be used to determine both the type of reactor and the initial fuel composition with good discrimination. Finally, partial least squares discriminant analysis (PSLDA) was investigated as a substitute for PCA. Our results suggest that PLSDA is a better tool for this application where separation between known classes is most important.
Three dimensional graphics in the statistical analysis of scientific data
Grotch, S.L.
1986-05-01
In scientific data analysis, the two-dimensional plot has become an indispensable tool. As the scientist more commonly encounters multivariate data, three dimensional graphics will form the natural extension of these more traditional representations. There can be little doubt that as the accessibility to ever more powerful graphics tools increases, their use will expand dramatically. In using three dimensional graphics in routine data analysis for nearly a decade, they have proved to be a powerful means for obtaining insights into data simply not available with traditional 2D methods. Examples of this work, taken primarily from chemistry and meteorology, are presented to illustrate a variety of 3D graphics found to be practically useful. Some approaches for improving these presentations are also highlighted.
Statistical theory and methodology for remote sensing data analysis
NASA Technical Reports Server (NTRS)
Odell, P. L.
1974-01-01
A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.
Practical guidance for statistical analysis of operational event data
Atwood, C.L.
1995-10-01
This report presents ways to avoid mistakes that are sometimes made in analysis of operational event data. It then gives guidance on what to do when a model is rejected, a list of standard types of models to consider, and principles for choosing one model over another. For estimating reliability, it gives advice on which failure modes to model, and moment formulas for combinations of failure modes. The issues are illustrated with many examples and case studies.
Advancing Usability Evaluation through Human Reliability Analysis
Ronald L. Boring; David I. Gertman
2005-07-01
This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.
Progress in Advanced Spectral Analysis of Radioxenon
Haas, Derek A.; Schrom, Brian T.; Cooper, Matthew W.; Ely, James H.; Flory, Adam E.; Hayes, James C.; Heimbigner, Tom R.; McIntyre, Justin I.; Saunders, Danielle L.; Suckow, Thomas J.
2010-09-21
Improvements to a Java based software package developed at Pacific Northwest National Laboratory (PNNL) for display and analysis of radioxenon spectra acquired by the International Monitoring System (IMS) are described here. The current version of the Radioxenon JavaViewer implements the region of interest (ROI) method for analysis of beta-gamma coincidence data. Upgrades to the Radioxenon JavaViewer will include routines to analyze high-purity germanium detector (HPGe) data, Standard Spectrum Method to analyze beta-gamma coincidence data and calibration routines to characterize beta-gamma coincidence detectors. These upgrades are currently under development; the status and initial results will be presented. Implementation of these routines into the JavaViewer and subsequent release is planned for FY 2011-2012.
Advanced CMOS Radiation Effects Testing Analysis
NASA Technical Reports Server (NTRS)
Pellish, Jonathan Allen; Marshall, Paul W.; Rodbell, Kenneth P.; Gordon, Michael S.; LaBel, Kenneth A.; Schwank, James R.; Dodds, Nathaniel A.; Castaneda, Carlos M.; Berg, Melanie D.; Kim, Hak S.; Phan, Anthony M.; Seidleck, Christina M.
2014-01-01
Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.
Advanced CMOS Radiation Effects Testing and Analysis
NASA Technical Reports Server (NTRS)
Pellish, J. A.; Marshall, P. W.; Rodbell, K. P.; Gordon, M. S.; LaBel, K. A.; Schwank, J. R.; Dodds, N. A.; Castaneda, C. M.; Berg, M. D.; Kim, H. S.; Phan, A. M.; Seidleck, C. M.
2014-01-01
Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.
Advanced Techniques for Root Cause Analysis
2000-09-19
Five items make up this package, or can be used individually. The Chronological Safety Management Template utilizes a linear adaptation of the Integrated Safety Management System laid out in the form of a template that greatly enhances the ability of the analyst to perform the first step of any investigation which is to gather all pertinent facts and identify causal factors. The Problem Analysis Tree is a simple three (3) level problem analysis tree whichmore » is easier for organizations outside of WSRC to use. Another part is the Systemic Root Cause Tree. One of the most basic and unique features of Expanded Root Cause Analysis is the Systemic Root Cause portion of the Expanded Root Cause Pyramid. The Systemic Root Causes are even more basic than the Programmatic Root Causes and represent Root Causes that cut across multiple (if not all) programs in an organization. the Systemic Root Cause portion contains 51 causes embedded at the bottom level of a three level Systemic Root Cause Tree that is divided into logical, organizationally based categorie to assist the analyst. The Computer Aided Root Cause Analysis that allows the analyst at each level of the Pyramid to a) obtain a brief description of the cause that is being considered, b) record a decision that the item is applicable, c) proceed to the next level of the Pyramid to see only those items at the next level of the tree that are relevant to the particular cause that has been chosen, and d) at the end of the process automatically print out a summary report of the incident, the causal factors as they relate to the safety management system, the probable causes, apparent causes, Programmatic Root Causes and Systemic Root Causes for each causal factor and the associated corrective action.« less
Advanced automated char image analysis techniques
Tao Wu; Edward Lester; Michael Cloke
2006-05-15
Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300{sup o}C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 {mu}m). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles. 20 refs., 10 figs., 3 tabs.
Measuring the Success of an Academic Development Programme: A Statistical Analysis
ERIC Educational Resources Information Center
Smith, L. C.
2009-01-01
This study uses statistical analysis to estimate the impact of first-year academic development courses in microeconomics, statistics, accountancy, and information systems, offered by the University of Cape Town's Commerce Academic Development Programme, on students' graduation performance relative to that achieved by mainstream students. The data…
A new statistic for the analysis of circular data in gamma-ray astronomy
NASA Technical Reports Server (NTRS)
Protheroe, R. J.
1985-01-01
A new statistic is proposed for the analysis of circular data. The statistic is designed specifically for situations where a test of uniformity is required which is powerful against alternatives in which a small fraction of the observations is grouped in a small range of directions, or phases.
ERIC Educational Resources Information Center
Papadimitriou, Fivos; Kidman, Gillian
2012-01-01
Certain statistic and scientometric features of articles published in the journal "International Research in Geographical and Environmental Education" (IRGEE) are examined in this paper for the period 1992-2009 by applying nonparametric statistics and Shannon's entropy (diversity) formula. The main findings of this analysis are: (a) after 2004,…
ERIC Educational Resources Information Center
Jones, Andrew T.
2011-01-01
Practitioners often depend on item analysis to select items for exam forms and have a variety of options available to them. These include the point-biserial correlation, the agreement statistic, the B index, and the phi coefficient. Although research has demonstrated that these statistics can be useful for item selection, no research as of yet has…
ERIC Educational Resources Information Center
Huston, Holly L.
This paper begins with a general discussion of statistical significance, effect size, and power analysis; and concludes by extending the discussion to the multivariate case (MANOVA). Historically, traditional statistical significance testing has guided researchers' thinking about the meaningfulness of their data. The use of significance testing…
Statistical correlation analysis for comparing vibration data from test and analysis
NASA Technical Reports Server (NTRS)
Butler, T. G.; Strang, R. F.; Purves, L. R.; Hershfeld, D. J.
1986-01-01
A theory was developed to compare vibration modes obtained by NASTRAN analysis with those obtained experimentally. Because many more analytical modes can be obtained than experimental modes, the analytical set was treated as expansion functions for putting both sources in comparative form. The dimensional symmetry was developed for three general cases: nonsymmetric whole model compared with a nonsymmetric whole structural test, symmetric analytical portion compared with a symmetric experimental portion, and analytical symmetric portion with a whole experimental test. The theory was coded and a statistical correlation program was installed as a utility. The theory is established with small classical structures.
NASA Astrophysics Data System (ADS)
Stefani, Jerry A.; Poarch, Scott; Saxena, Sharad; Mozumder, P. K.
1994-09-01
An advanced multivariable off-line process control system, which combines traditional Statistical Process Control (SPC) with feedback control, has been applied to the CVD tungsten process on an Applied Materials Centura reactor. The goal of the model-based controller is to compensate for shifts in the process and maintain the wafer state responses on target. In the present application the controller employs measurements made on test wafers by off-line metrology tools to track the process behavior. This is accomplished by using model- bases SPC, which compares the measurements with predictions obtained from empirically-derived process models. For CVD tungsten, a physically-based modeling approach was employed based on the kinetically-limited H2 reduction of WF6. On detecting a statistically significant shift in the process, the controller calculates adjustments to the settings to bring the process responses back on target. To achieve this a few additional test wafers are processed at slightly different settings than the nominal. This local experiment allows the models to be updated to reflect the current process performance. The model updates are expressed as multiplicative or additive changes in the process inputs and a change in the model constant. This approach for model updating not only tracks the present process/equipment state, but it also provides some diagnostic capability regarding the cause of the process shift. The updated models are used by an optimizer to compute new settings to bring the responses back to target. The optimizer is capable of incrementally entering controllables into the strategy, reflecting the degree to which the engineer desires to manipulates each setting. The capability of the controller to compensate for shifts in the CVD tungsten process has been demonstrated. Targets for film bulk resistivity and deposition rate were maintained while satisfying constraints on film stress and WF6 conversion efficiency.
ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization
NASA Astrophysics Data System (ADS)
Antcheva, I.; Ballintijn, M.; Bellenot, B.; Biskup, M.; Brun, R.; Buncic, N.; Canal, Ph.; Casadei, D.; Couet, O.; Fine, V.; Franco, L.; Ganis, G.; Gheata, A.; Maline, D. Gonzalez; Goto, M.; Iwaszkiewicz, J.; Kreshuk, A.; Segura, D. Marcos; Maunder, R.; Moneta, L.; Naumann, A.; Offermann, E.; Onuchin, V.; Panacek, S.; Rademakers, F.; Russo, P.; Tadel, M.
2009-12-01
ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, the RooFit package allows the user to perform complex data modeling and fitting while the RooStats library provides abstractions and implementations for advanced statistical tools. Multivariate classification methods based on machine learning techniques are available via the TMVA package. A central piece in these analysis tools are the histogram classes which provide binning of one- and multi-dimensional data. Results can be saved in high-quality graphical formats like Postscript and PDF or in bitmap formats like JPG or GIF. The result can also be stored into ROOT macros that allow a full recreation and rework of the graphics. Users typically create their analysis macros step by step, making use of the interactive C++ interpreter CINT, while running over small data samples. Once the development is finished, they can run these macros at full compiled speed over large data sets, using on-the-fly compilation, or by creating a stand-alone batch program. Finally, if processing farms are available, the user can reduce the execution time of intrinsically parallel tasks — e.g. data mining in HEP — by using PROOF, which will take care of optimally
Analysis of compressive fracture in rock using statistical techniques
Blair, S.C.
1994-12-01
Fracture of rock in compression is analyzed using a field-theory model, and the processes of crack coalescence and fracture formation and the effect of grain-scale heterogeneities on macroscopic behavior of rock are studied. The model is based on observations of fracture in laboratory compression tests, and incorporates assumptions developed using fracture mechanics analysis of rock fracture. The model represents grains as discrete sites, and uses superposition of continuum and crack-interaction stresses to create cracks at these sites. The sites are also used to introduce local heterogeneity. Clusters of cracked sites can be analyzed using percolation theory. Stress-strain curves for simulated uniaxial tests were analyzed by studying the location of cracked sites, and partitioning of strain energy for selected intervals. Results show that the model implicitly predicts both development of shear-type fracture surfaces and a strength-vs-size relation that are similar to those observed for real rocks. Results of a parameter-sensitivity analysis indicate that heterogeneity in the local stresses, attributed to the shape and loading of individual grains, has a first-order effect on strength, and that increasing local stress heterogeneity lowers compressive strength following an inverse power law. Peak strength decreased with increasing lattice size and decreasing mean site strength, and was independent of site-strength distribution. A model for rock fracture based on a nearest-neighbor algorithm for stress redistribution is also presented and used to simulate laboratory compression tests, with promising results.
Statistical methods for the forensic analysis of striated tool marks
Hoeksema, Amy Beth
2013-01-01
In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.
Egorova, K S; Kondakova, A N; Toukach, Ph V
2015-01-01
Carbohydrates are biological blocks participating in diverse and crucial processes both at cellular and organism levels. They protect individual cells, establish intracellular interactions, take part in the immune reaction and participate in many other processes. Glycosylation is considered as one of the most important modifications of proteins and other biologically active molecules. Still, the data on the enzymatic machinery involved in the carbohydrate synthesis and processing are scattered, and the advance on its study is hindered by the vast bulk of accumulated genetic information not supported by any experimental evidences for functions of proteins that are encoded by these genes. In this article, we present novel instruments for statistical analysis of glycomes in taxa. These tools may be helpful for investigating carbohydrate-related enzymatic activities in various groups of organisms and for comparison of their carbohydrate content. The instruments are developed on the Carbohydrate Structure Database (CSDB) platform and are available freely on the CSDB web-site at http://csdb.glycoscience.ru. Database URL: http://csdb.glycoscience.ru. PMID:26337239
Egorova, K.S.; Kondakova, A.N.; Toukach, Ph.V.
2015-01-01
Carbohydrates are biological blocks participating in diverse and crucial processes both at cellular and organism levels. They protect individual cells, establish intracellular interactions, take part in the immune reaction and participate in many other processes. Glycosylation is considered as one of the most important modifications of proteins and other biologically active molecules. Still, the data on the enzymatic machinery involved in the carbohydrate synthesis and processing are scattered, and the advance on its study is hindered by the vast bulk of accumulated genetic information not supported by any experimental evidences for functions of proteins that are encoded by these genes. In this article, we present novel instruments for statistical analysis of glycomes in taxa. These tools may be helpful for investigating carbohydrate-related enzymatic activities in various groups of organisms and for comparison of their carbohydrate content. The instruments are developed on the Carbohydrate Structure Database (CSDB) platform and are available freely on the CSDB web-site at http://csdb.glycoscience.ru. Database URL: http://csdb.glycoscience.ru PMID:26337239
Statistical analysis of the ambiguities in the asteroid period determinations
NASA Astrophysics Data System (ADS)
Butkiewicz, M.; Kwiatkowski, T.; Bartczak, P.; Dudziński, G.
2014-07-01
A synodic period of an asteroid can be derived from its lightcurve by standard methods like Fourier-series fitting. A problem appears when results of observations are based on less than a full coverage of a lightcurve and/or high level of noise. Also, long gaps between individual lightcurves create an ambiguity in the cycle count which leads to aliases. Excluding binary systems and objects with non-principal-axis rotation, the rotation period is usually identical to the period of the second Fourier harmonic of the lightcurve. There are cases, however, where it may be connected with the 1st, 3rd, or 4th harmonic and it is difficult to choose among them when searching for the period. To help remove such uncertainties we analysed asteroid lightcurves for a range of shapes and observing/illuminating geometries. We simulated them using a modified internal code from the ISAM service (Marciniak et al. 2012, A&A 545, A131). In our computations, shapes of asteroids were modeled as Gaussian random spheres (Muinonen 1998, A&A, 332, 1087). A combination of Lommel-Seeliger and Lambert scattering laws was assumed. For each of the 100 shapes, we randomly selected 1000 positions of the spin axis, systematically changing the solar phase angle with a step of 5°. For each lightcurve, we determined its peak-to-peak amplitude, fitted the 6th-order Fourier series and derived the amplitudes of its harmonics. Instead of the number of the lightcurve extrema, which in many cases is subjective, we characterized each lightcurve by the order of the highest-amplitude Fourier harmonic. The goal of our simulations was to derive statistically significant conclusions (based on the underlying assumptions) about the dominance of different harmonics in the lightcurves of the specified amplitude and phase angle. The results, presented in the Figure, can be used in individual cases to estimate the probability that the obtained lightcurve is dominated by a specified Fourier harmonic. Some of the
Advanced Orion Optimized Laser System Analysis
NASA Technical Reports Server (NTRS)
1996-01-01
Contractor shall perform a complete analysis of the potential of the solid state laser in the very long pulse mode (100 ns pulse width, 10-30 hz rep-rate) and in the very short pulse mode (100 ps pulse width 10-30 hz rep rate) concentrating on the operation of the device in the 'hot-rod' mode, where no active cooling the laser operation is attempted. Contractor's calculations shall be made of the phase aberrations which develop during the repped-pulse train, and the results shall feed into the adaptive optics analyses. The contractor shall devise solutions to work around ORION track issues. A final report shall be furnished to the MSFC COTR including all calculations and analysis of estimates of bulk phase and intensity aberration distribution in the laser output beam as a function of time during the repped-pulse train for both wave forms (high-energy/long-pulse, as well as low-energy/short-pulse). Recommendations shall be made for mitigating the aberrations by laser re-design and/or changes in operating parameters of optical pump sources and/or designs.
Statistical Analysis Strategies for Association Studies Involving Rare Variants
Bansal, Vikas; Libiger, Ondrej; Torkamani, Ali; Schork, Nicholas J.
2013-01-01
The limitations of genome-wide association (GWA) studies that focus on the phenotypic influence of common genetic variants have motivated human geneticists to consider the contribution of rare variants to phenotypic expression. The increasing availability of high-throughput sequencing technology has enabled studies of rare variants, but will not be sufficient for their success since appropriate analytical methods are also needed. We consider data analysis approaches to testing associations between a phenotype and collections of rare variants in a defined genomic region or set of regions. Ultimately, although a wide variety of analytical approaches exist, more work is needed to refine them and determine their properties and power in different contexts. PMID:20940738
STATISTICAL ANALYSIS OF THE VERY QUIET SUN MAGNETISM
Martinez Gonzalez, M. J.; Manso Sainz, R.; Asensio Ramos, A.
2010-03-10
The behavior of the observed polarization amplitudes with spatial resolution is a strong constraint on the nature and organization of solar magnetic fields below the resolution limit. We study the polarization of the very quiet Sun at different spatial resolutions using ground- and space-based observations. It is shown that 80% of the observed polarization signals do not change with spatial resolution, suggesting that, observationally, the very quiet Sun magnetism remains the same despite the high spatial resolution of space-based observations. Our analysis also reveals a cascade of spatial scales for the magnetic field within the resolution element. It is manifest that the Zeeman effect is sensitive to the microturbulent field usually associated with Hanle diagnostics. This demonstrates that Zeeman and Hanle studies show complementary perspectives of the same magnetism.
Statistical Analysis of Factors Affecting Child Mortality in Pakistan.
Ahmed, Zoya; Kamal, Asifa; Kamal, Asma
2016-06-01
Child mortality is a composite indicator reflecting economic, social, environmental, healthcare services, and their delivery situation in a country. Globally, Pakistan has the third highest burden of fetal, maternal, and child mortality. Factors affecting child mortality in Pakistan are investigated by using Binary Logistic Regression Analysis. Region, education of mother, birth order, preceding birth interval (the period between the previous child birth and the index child birth), size of child at birth, and breastfeeding and family size were found to be significantly important with child mortality in Pakistan. Child mortality decreased as level of mother's education, preceding birth interval, size of child at birth, and family size increased. Child mortality was found to be significantly higher in Balochistan as compared to other regions. Child mortality was low for low birth orders. Child survival was significantly higher for children who were breastfed as compared to those who were not.
Statistical analysis of the temporal properties of BL Lacertae
NASA Astrophysics Data System (ADS)
Guo, Yu Cheng; Hu, Shao Ming; Li, Yu Tong; Chen, Xu
2016-08-01
A comprehensive temporal analysis has been performed on optical light curves of BL Lacertae in the B, V and R bands. The light curves were denoised by Gaussian smoothing and decomposed into individual flares using an exponential profile. The asymmetry, duration, peak flux and equivalent energy output of flares were measured and the frequency distributions presented. Most optical flares of BL Lacertae are highly symmetric, with a weak tendency towards gradual rises and rapid decays. The distribution of flare durations is not random, but consistent with a gamma distribution. Peak fluxes and energy outputs of flares all follow a log-normal distribution. A positive correlation is detected between flare durations and peak fluxes. The temporal properties of BL Lacertae provide evidence of the stochastic magnetohydrodynamic process in the accretion disc and jet.The results presented here can serve as constraints on physical models attempting to interpret blazar variations.
Spectral reflectance of surface soils - A statistical analysis
NASA Technical Reports Server (NTRS)
Crouse, K. R.; Henninger, D. L.; Thompson, D. R.
1983-01-01
The relationship of the physical and chemical properties of soils to their spectral reflectance as measured at six wavebands of Thematic Mapper (TM) aboard NASA's Landsat-4 satellite was examined. The results of performing regressions of over 20 soil properties on the six TM bands indicated that organic matter, water, clay, cation exchange capacity, and calcium were the properties most readily predicted from TM data. The middle infrared bands, bands 5 and 7, were the best bands for predicting soil properties, and the near infrared band, band 4, was nearly as good. Clustering 234 soil samples on the TM bands and characterizing the clusters on the basis of soil properties revealed several clear relationships between properties and reflectance. Discriminant analysis found organic matter, fine sand, base saturation, sand, extractable acidity, and water to be significant in discriminating among clusters.
Fine needle aspiration biopsy diagnosis of mucoepidermoid carcinoma. Statistical analysis.
Cohen, M B; Fisher, P E; Holly, E A; Ljung, B M; Löwhagen, T; Bottles, K
1990-01-01
Fine needle aspiration (FNA) biopsy is an increasingly popular method for the evaluation of salivary gland tumors. Of the common salivary gland tumors, mucoepidermoid carcinoma is probably the most difficult to diagnose accurately by this means. A series of 96 FNA biopsy specimens of salivary gland masses, including 34 mucoepidermoid carcinomas, 51 other benign and malignant neoplasms, 7 nonneoplastic lesions and 4 normal salivary glands, were analyzed in order to identify the most useful criteria for diagnosing mucoepidermoid carcinoma. Thirteen cytologic criteria were evaluated in the FNA specimens, and a stepwise logistic regression analysis was performed. The three cytologic features selected as most predictive of mucoepidermoid carcinoma were intermediate cells, squamous cells and overlapping epithelial groups. Using these three features together, the sensitivity and specificity of accurately diagnosing mucoepidermoid carcinoma were 97% and 100%, respectively.
Ordinary chondrites - Multivariate statistical analysis of trace element contents
NASA Technical Reports Server (NTRS)
Lipschutz, Michael E.; Samuels, Stephen M.
1991-01-01
The contents of mobile trace elements (Co, Au, Sb, Ga, Se, Rb, Cs, Te, Bi, Ag, In, Tl, Zn, and Cd) in Antarctic and non-Antarctic populations of H4-6 and L4-6 chondrites, were compared using standard multivariate discriminant functions borrowed from linear discriminant analysis and logistic regression. A nonstandard randomization-simulation method was developed, making it possible to carry out probability assignments on a distribution-free basis. Compositional differences were found both between the Antarctic and non-Antarctic H4-6 chondrite populations and between two L4-6 chondrite populations. It is shown that, for various types of meteorites (in particular, for the H4-6 chondrites), the Antarctic/non-Antarctic compositional difference is due to preterrestrial differences in the genesis of their parent materials.
Statistical Analysis of Temple Orientation in Ancient India
NASA Astrophysics Data System (ADS)
Aller, Alba; Belmonte, Juan Antonio
2015-05-01
The great diversity of religions that have been followed in India for over 3000 years is the reason why there are hundreds of temples built to worship dozens of different divinities. In this work, more than one hundred temples geographically distributed over the whole Indian land have been analyzed, obtaining remarkable results. For this purpose, a deep analysis of the main deities who are worshipped in each of them, as well as of the different dynasties (or cultures) who built them has also been conducted. As a result, we have found that the main axes of the temples dedicated to Shiva seem to be oriented to the east cardinal point while those temples dedicated to Vishnu would be oriented to both the east and west cardinal points. To explain these cardinal directions we propose to look back to the origins of Hinduism. Besides these cardinal orientations, clear solar orientations have also been found, especially at the equinoctial declination.
Statistical Analysis of Acoustic Wave Parameters Near Solar Active Regions
NASA Astrophysics Data System (ADS)
Rabello-Soares, M. Cristina; Bogart, Richard S.; Scherrer, Philip H.
2016-08-01
In order to quantify the influence of magnetic fields on acoustic mode parameters and flows in and around active regions, we analyze the differences in the parameters in magnetically quiet regions nearby an active region (which we call “nearby regions”), compared with those of quiet regions at the same disk locations for which there are no neighboring active regions. We also compare the mode parameters in active regions with those in comparably located quiet regions. Our analysis is based on ring-diagram analysis of all active regions observed by the Helioseismic and Magnetic Imager (HMI) during almost five years. We find that the frequency at which the mode amplitude changes from attenuation to amplification in the quiet nearby regions is around 4.2 mHz, in contrast to the active regions, for which it is about 5.1 mHz. This amplitude enhacement (the “acoustic halo effect”) is as large as that observed in the active regions, and has a very weak dependence on the wave propagation direction. The mode energy difference in nearby regions also changes from a deficit to an excess at around 4.2 mHz, but averages to zero over all modes. The frequency difference in nearby regions increases with increasing frequency until a point at which the frequency shifts turn over sharply, as in active regions. However, this turnover occurs around 4.9 mHz, which is significantly below the acoustic cutoff frequency. Inverting the horizontal flow parameters in the direction of the neigboring active regions, we find flows that are consistent with a model of the thermal energy flow being blocked directly below the active region.
Statistical analysis of large-scale neuronal recording data
Reed, Jamie L.; Kaas, Jon H.
2010-01-01
Relating stimulus properties to the response properties of individual neurons and neuronal networks is a major goal of sensory research. Many investigators implant electrode arrays in multiple brain areas and record from chronically implanted electrodes over time to answer a variety of questions. Technical challenges related to analyzing large-scale neuronal recording data are not trivial. Several analysis methods traditionally used by neurophysiologists do not account for dependencies in the data that are inherent in multi-electrode recordings. In addition, when neurophysiological data are not best modeled by the normal distribution and when the variables of interest may not be linearly related, extensions of the linear modeling techniques are recommended. A variety of methods exist to analyze correlated data, even when data are not normally distributed and the relationships are nonlinear. Here we review expansions of the Generalized Linear Model designed to address these data properties. Such methods are used in other research fields, and the application to large-scale neuronal recording data will enable investigators to determine the variable properties that convincingly contribute to the variances in the observed neuronal measures. Standard measures of neuron properties such as response magnitudes can be analyzed using these methods, and measures of neuronal network activity such as spike timing correlations can be analyzed as well. We have done just that in recordings from 100-electrode arrays implanted in the primary somatosensory cortex of owl monkeys. Here we illustrate how one example method, Generalized Estimating Equations analysis, is a useful method to apply to large-scale neuronal recordings. PMID:20472395
Multiple outcomes are often measured on each experimental unit in toxicology experiments. These multiple observations typically imply the existence of correlation between endpoints, and a statistical analysis that incorporates it may result in improved inference. When both disc...
Advanced stability analysis for laminar flow control
NASA Technical Reports Server (NTRS)
Orszag, S. A.
1981-01-01
Five classes of problems are addressed: (1) the extension of the SALLY stability analysis code to the full eighth order compressible stability equations for three dimensional boundary layer; (2) a comparison of methods for prediction of transition using SALLY for incompressible flows; (3) a study of instability and transition in rotating disk flows in which the effects of Coriolis forces and streamline curvature are included; (4) a new linear three dimensional instability mechanism that predicts Reynolds numbers for transition to turbulence in planar shear flows in good agreement with experiment; and (5) a study of the stability of finite amplitude disturbances in axisymmetric pipe flow showing the stability of this flow to all nonlinear axisymmetric disturbances.
Value analysis for advanced technology products
NASA Astrophysics Data System (ADS)
Soulliere, Mark
2011-03-01
Technology by itself can be wondrous, but buyers of technology factor in the price they have to pay along with performance in their decisions. As a result, the ``best'' technology may not always win in the marketplace when ``good enough'' can be had at a lower price. Technology vendors often set pricing by ``cost plus margin,'' or by competitors' offerings. What if the product is new (or has yet to be invented)? Value pricing is a methodology to price products based on the value generated (e.g. money saved) by using one product vs. the next best technical alternative. Value analysis can often clarify what product attributes generate the most value. It can also assist in identifying market forces outside of the control of the technology vendor that also influence pricing. These principles are illustrated with examples.
Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs
Tang, Zheng-Zheng; Lin, Dan-Yu
2015-01-01
There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that meta-analysis based on properly calculated summary statistics is as powerful as joint analysis of individual-participant data. In addition, we demonstrate the performance of different meta-analysis methods by using both simulated and empirical data. We then compare four major software packages for meta-analysis of rare-variant associations—MASS, RAREMETAL, MetaSKAT, and seqMeta—in terms of the underlying statistical methodology, analysis pipeline, and software interface. Finally, we present PreMeta, a software interface that integrates the four meta-analysis packages and allows a consortium to combine otherwise incompatible summary statistics. PMID:26094574
Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.
Tang, Zheng-Zheng; Lin, Dan-Yu
2015-07-01
There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that meta-analysis based on properly calculated summary statistics is as powerful as joint analysis of individual-participant data. In addition, we demonstrate the performance of different meta-analysis methods by using both simulated and empirical data. We then compare four major software packages for meta-analysis of rare-variant associations-MASS, RAREMETAL, MetaSKAT, and seqMeta-in terms of the underlying statistical methodology, analysis pipeline, and software interface. Finally, we present PreMeta, a software interface that integrates the four meta-analysis packages and allows a consortium to combine otherwise incompatible summary statistics.
Methods of learning in statistical education: Design and analysis of a randomized trial
NASA Astrophysics Data System (ADS)
Boyd, Felicity Turner
Background. Recent psychological and technological advances suggest that active learning may enhance understanding and retention of statistical principles. A randomized trial was designed to evaluate the addition of innovative instructional methods within didactic biostatistics courses for public health professionals. Aims. The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance; assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. Methods. Consenting students enrolled in a graduate introductory biostatistics course were randomized to cooperative learning, internet learning, or control after completing a pretest survey. The cooperative learning group participated in eight small group active learning sessions on key statistical concepts, while the internet learning group accessed interactive mini-applications on the same concepts. Controls received no intervention. Students completed evaluations after each session and a post-test survey. Study outcome was performance quantified by examination scores. Intervention effects were analyzed by generalized linear models using intent-to-treat analysis and marginal structural models accounting for reported participation. Results. Of 376 enrolled students, 265 (70%) consented to randomization; 69, 100, and 96 students were randomized to the cooperative, internet, and control groups, respectively. Intent-to-treat analysis showed no differences between study groups; however, 51% of students in the intervention groups had dropped out after the second session. After accounting for reported participation, expected examination scores were 2.6 points higher (of 100 points) after completing one cooperative learning session (95% CI: 0.3, 4.9) and 2.4 points higher after one internet learning session (95% CI: 0.0, 4.7), versus
Statistical analysis of low-voltage EDS spectrum images
Anderson, I.M.
1998-03-01
The benefits of using low ({le}5 kV) operating voltages for energy-dispersive X-ray spectrometry (EDS) of bulk specimens have been explored only during the last few years. This paper couples low-voltage EDS with two other emerging areas of characterization: spectrum imaging of a computer chip manufactured by a major semiconductor company. Data acquisition was performed with a Philips XL30-FEG SEM operated at 4 kV and equipped with an Oxford super-ATW detector and XP3 pulse processor. The specimen was normal to the electron beam and the take-off angle for acquisition was 35{degree}. The microscope was operated with a 150 {micro}m diameter final aperture at spot size 3, which yielded an X-ray count rate of {approximately}2,000 s{sup {minus}1}. EDS spectrum images were acquired as Adobe Photoshop files with the 4pi plug-in module. (The spectrum images could also be stored as NIH Image files, but the raw data are automatically rescaled as maximum-contrast (0--255) 8-bit TIFF images -- even at 16-bit resolution -- which poses an inconvenience for quantitative analysis.) The 4pi plug-in module is designed for EDS X-ray mapping and allows simultaneous acquisition of maps from 48 elements plus an SEM image. The spectrum image was acquired by re-defining the energy intervals of 48 elements to form a series of contiguous 20 eV windows from 1.25 kV to 2.19 kV. A spectrum image of 450 x 344 pixels was acquired from the specimen with a sampling density of 50 nm/pixel and a dwell time of 0.25 live seconds per pixel, for a total acquisition time of {approximately}14 h. The binary data files were imported into Mathematica for analysis with software developed by the author at Oak Ridge National Laboratory. A 400 x 300 pixel section of the original image was analyzed. MSA required {approximately}185 Mbytes of memory and {approximately}18 h of CPU time on a 300 MHz Power Macintosh 9600.
Integrated Data Collection Analysis (IDCA) Program - Statistical Analysis of RDX Standard Data Sets
Sandstrom, Mary M.; Brown, Geoffrey W.; Preston, Daniel N.; Pollard, Colin J.; Warner, Kirstin F.; Sorensen, Daniel N.; Remmers, Daniel L.; Phillips, Jason J.; Shelley, Timothy J.; Reyes, Jose A.; Hsu, Peter C.; Reynolds, John G.
2015-10-30
The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard. The material was tested as a well-characterized standard several times during the proficiency study to assess differences among participants and the range of results that may arise for well-behaved explosive materials. The analyses show that there are detectable differences among the results from IDCA participants. While these differences are statistically significant, most of them can be disregarded for comparison purposes to assess potential variability when laboratories attempt to measure identical samples using methods assumed to be nominally the same. The results presented in this report include the average sensitivity results for the IDCA participants and the ranges of values obtained. The ranges represent variation about the mean values of the tests of between 26% and 42%. The magnitude of this variation is attributed to differences in operator, method, and environment as well as the use of different instruments that are also of varying age. The results appear to be a good representation of the broader safety testing community based on the range of methods, instruments, and environments included in the IDCA Proficiency Test.
Wheat signature modeling and analysis for improved training statistics
NASA Technical Reports Server (NTRS)
Nalepka, R. F. (Principal Investigator); Malila, W. A.; Cicone, R. C.; Gleason, J. M.
1976-01-01
The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important.
NASA Astrophysics Data System (ADS)
Stewart, Brent K.; Carter, Stephen J.; Langer, Steven G.; Andrew, Rex K.
1998-06-01
Experiments using NASA's Advanced Communications Technology Satellite were conducted to provide an estimate of the compressed video quality required for preservation of clinically relevant features for the detection of trauma. Bandwidth rates of 128, 256 and 384 kbps were used. A five point Likert scale (1 equals no useful information and 5 equals good diagnostic quality) was used for a subjective preference questionnaire to evaluate the quality of the compressed ultrasound imagery at the three compression rates for several anatomical regions of interest. At 384 kbps the Likert scores (mean plus or minus SD) were abdomen (4.45 plus or minus 0.71), carotid artery (4.70 plus or minus 0.36), kidney (5.0 plus or minus 0.0), liver (4.67 plus or minus 0.58) and thyroid (4.03 plus or minus 0.74). Due to the volatile nature of the H.320 compressed digital video stream, no statistically significant results can be derived through this methodology. As the MPEG standard has at its roots many of the same intraframe and motion vector compression algorithms as the H.261 (such as that used in the previous ACTS/AMT experiments), we are using the MPEG compressed video sequences to best gauge what minimum bandwidths are necessary for preservation of clinically relevant features for the detection of trauma. We have been using an MPEG codec board to collect losslessly compressed video clips from high quality S- VHS tapes and through direct digitization of S-video. Due to the large number of videoclips and questions to be presented to the radiologists and for ease of application, we have developed a web browser interface for this video visual perception study. Due to the large numbers of observations required to reach statistical significance in most ROC studies, Kappa statistical analysis is used to analyze the degree of agreement between observers and between viewing assessment. If the degree of agreement amongst readers is high, then there is a possibility that the ratings (i
Multispectral laser imaging for advanced food analysis
NASA Astrophysics Data System (ADS)
Senni, L.; Burrascano, P.; Ricci, M.
2016-07-01
A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.
Advanced analysis techniques for uranium assay
Geist, W. H.; Ensslin, Norbert; Carrillo, L. A.; Beard, C. A.
2001-01-01
Uranium has a negligible passive neutron emission rate making its assay practicable only with an active interrogation method. The active interrogation uses external neutron sources to induce fission events in the uranium in order to determine the mass. This technique requires careful calibration with standards that are representative of the items to be assayed. The samples to be measured are not always well represented by the available standards which often leads to large biases. A technique of active multiplicity counting is being developed to reduce some of these assay difficulties. Active multiplicity counting uses the measured doubles and triples count rates to determine the neutron multiplication (f4) and the product of the source-sample coupling ( C ) and the 235U mass (m). Since the 35U mass always appears in the multiplicity equations as the product of Cm, the coupling needs to be determined before the mass can be known. A relationship has been developed that relates the coupling to the neutron multiplication. The relationship is based on both an analytical derivation and also on empirical observations. To determine a scaling constant present in this relationship, known standards must be used. Evaluation of experimental data revealed an improvement over the traditional calibration curve analysis method of fitting the doubles count rate to the 235Um ass. Active multiplicity assay appears to relax the requirement that the calibration standards and unknown items have the same chemical form and geometry.
Advances in carbonate exploration and reservoir analysis
Garland, J.; Neilson, J.; Laubach, S.E.; Whidden, Katherine J.
2012-01-01
The development of innovative techniques and concepts, and the emergence of new plays in carbonate rocks are creating a resurgence of oil and gas discoveries worldwide. The maturity of a basin and the application of exploration concepts have a fundamental influence on exploration strategies. Exploration success often occurs in underexplored basins by applying existing established geological concepts. This approach is commonly undertaken when new basins ‘open up’ owing to previous political upheavals. The strategy of using new techniques in a proven mature area is particularly appropriate when dealing with unconventional resources (heavy oil, bitumen, stranded gas), while the application of new play concepts (such as lacustrine carbonates) to new areas (i.e. ultra-deep South Atlantic basins) epitomizes frontier exploration. Many low-matrix-porosity hydrocarbon reservoirs are productive because permeability is controlled by fractures and faults. Understanding basic fracture properties is critical in reducing geological risk and therefore reducing well costs and increasing well recovery. The advent of resource plays in carbonate rocks, and the long-standing recognition of naturally fractured carbonate reservoirs means that new fracture and fault analysis and prediction techniques and concepts are essential.
Statistical analysis of molecular nanotemplate driven DNA adsorption on graphite.
Dubrovin, E V; Speller, S; Yaminsky, I V
2014-12-30
In this work, we have studied the conformation of DNA molecules aligned on the nanotemplates of octadecylamine, stearyl alcohol, and stearic acid on highly oriented pyrolytic graphite (HOPG). For this purpose, fluctuations of contours of adsorbed biopolymers obtained from atomic force microscopy (AFM) images were analyzed using the wormlike chain model. Moreover, the conformations of adsorbed biopolymer molecules were characterized by the analysis of the scaling exponent ν, which relates the mean squared end-to-end distance and contour length of the polymer. During adsorption on octadecylamine and stearyl alcohol nanotemplates, DNA forms straight segments, which order along crystallographic axes of graphite. In this case, the conformation of DNA molecules can be described using two different length scales. On a large length scale (at contour lengths l > 200-400 nm), aligned DNA molecules have either 2D compact globule or partially relaxed 2D conformation, whereas on a short length scale (at l ≤ 200-400 nm) their conformation is close to that of rigid rods. The latter type of conformation can be also assigned to DNA adsorbed on a stearic acid nanotemplate. The different conformation of DNA molecules observed on the studied monolayers is connected with the different DNA-nanotemplate interactions associated with the nature of the functional group of the alkane derivative in the nanotemplate (amine, alcohol, or acid). The persistence length of λ-DNA adsorbed on octadecylamine nanotemplates is 31 ± 2 nm indicating the loss of DNA rigidity in comparison with its native state. Similar values of the persistence length (34 ± 2 nm) obtained for 24-times shorter DNA molecules adsorbed on an octadecylamine nanotemplate demonstrate that this rigidity change does not depend on biopolymer length. Possible reasons for the reduction of DNA persistence length are discussed in view of the internal DNA structure and DNA-surface interaction.
Processing and statistical analysis of soil-root images
NASA Astrophysics Data System (ADS)
Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov
2016-04-01
Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.
Advanced computational tools for 3-D seismic analysis
Barhen, J.; Glover, C.W.; Protopopescu, V.A.
1996-06-01
The global objective of this effort is to develop advanced computational tools for 3-D seismic analysis, and test the products using a model dataset developed under the joint aegis of the United States` Society of Exploration Geophysicists (SEG) and the European Association of Exploration Geophysicists (EAEG). The goal is to enhance the value to the oil industry of the SEG/EAEG modeling project, carried out with US Department of Energy (DOE) funding in FY` 93-95. The primary objective of the ORNL Center for Engineering Systems Advanced Research (CESAR) is to spearhead the computational innovations techniques that would enable a revolutionary advance in 3-D seismic analysis. The CESAR effort is carried out in collaboration with world-class domain experts from leading universities, and in close coordination with other national laboratories and oil industry partners.
NASA Technical Reports Server (NTRS)
Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.
2011-01-01
Comet Enflow is a commercially available, high frequency vibroacoustic analysis software founded on Energy Finite Element Analysis (EFEA) and Energy Boundary Element Analysis (EBEA). Energy Finite Element Analysis (EFEA) was validated on a floor-equipped composite cylinder by comparing EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) and experimental results. Statistical Energy Analysis (SEA) predictions were made using the commercial software program VA One 2009 from ESI Group. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 100 Hz to 4000 Hz.
NASTRAN documentation for flutter analysis of advanced turbopropellers
NASA Technical Reports Server (NTRS)
Elchuri, V.; Gallo, A. M.; Skalski, S. C.
1982-01-01
An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs was modified to facilitate investigation of the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) varying sweep.
METHODS ADVANCEMENT FOR MILK ANALYSIS: THE MAMA STUDY
The Methods Advancement for Milk Analysis (MAMA) study was designed by US EPA and CDC investigators to provide data to support the technological and study design needs of the proposed National Children=s Study (NCS). The NCS is a multi-Agency-sponsored study, authorized under the...
Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis
ERIC Educational Resources Information Center
Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.
2006-01-01
Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…
Polybrominated Diphenyl Ethers in Dryer Lint: An Advanced Analysis Laboratory
ERIC Educational Resources Information Center
Thompson, Robert Q.
2008-01-01
An advanced analytical chemistry laboratory experiment is described that involves environmental analysis and gas chromatography-mass spectrometry. Students analyze lint from clothes dryers for traces of flame retardant chemicals, polybrominated diphenylethers (PBDEs), compounds receiving much attention recently. In a typical experiment, ng/g…
Feasibility of voxel-based statistical analysis method for myocardial PET
NASA Astrophysics Data System (ADS)
Ram Yu, A.; Kim, Jin Su; Paik, Chang H.; Kim, Kyeong Min; Moo Lim, Sang
2014-09-01
Although statistical parametric mapping (SPM) analysis is widely used in neuroimaging studies, to our best knowledge, there was no application to myocardial PET data analysis. In this study, we developed the voxel based statistical analysis method for myocardial PET which provides statistical comparison results between groups in image space. PET Emission data of normal and myocardial infarction rats were acquired For the SPM analysis, a rat heart template was created. In addition, individual PET data was spatially normalized and smoothed. Two sample t-tests were performed to identify the myocardial infarct region. This developed SPM method was compared with conventional ROI methods. Myocardial glucose metabolism was decreased in the lateral wall of the left ventricle. In the result of ROI analysis, the mean value of the lateral wall was 29% decreased. The newly developed SPM method for myocardial PET could provide quantitative information in myocardial PET study.
Advanced stress analysis methods applicable to turbine engine structures
NASA Technical Reports Server (NTRS)
Pian, T. H. H.
1985-01-01
Advanced stress analysis methods applicable to turbine engine structures are investigated. Constructions of special elements which containing traction-free circular boundaries are investigated. New versions of mixed variational principle and version of hybrid stress elements are formulated. A method is established for suppression of kinematic deformation modes. semiLoof plate and shell elements are constructed by assumed stress hybrid method. An elastic-plastic analysis is conducted by viscoplasticity theory using the mechanical subelement model.
Recent Advances in Multidisciplinary Analysis and Optimization, part 1
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M. (Editor)
1989-01-01
This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.
Recent Advances in Multidisciplinary Analysis and Optimization, part 3
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M. (Editor)
1989-01-01
This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.
Recent Advances in Multidisciplinary Analysis and Optimization, part 2
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M. (Editor)
1989-01-01
This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.
Bell, B Sue; Hoskins, Richard E; Pickle, Linda Williams; Wartenberg, Daniel
2006-01-01
Background To communicate population-based cancer statistics, cancer researchers have a long tradition of presenting data in a spatial representation, or map. Historically, health data were presented in printed atlases in which the map producer selected the content and format. The availability of geographic information systems (GIS) with comprehensive mapping and spatial analysis capability for desktop and Internet mapping has greatly expanded the number of producers and consumers of health maps, including policymakers and the public. Because health maps, particularly ones that show elevated cancer rates, historically have raised public concerns, it is essential that these maps be designed to be accurate, clear, and interpretable for the broad range of users who may view them. This article focuses on designing maps to communicate effectively. It is based on years of research into the use of health maps for communicating among public health researchers. Results The basics for designing maps that communicate effectively are similar to the basics for any mode of communication. Tasks include deciding on the purpose, knowing the audience and its characteristics, choosing a media suitable for both the purpose and the audience, and finally testing the map design to ensure that it suits the purpose with the intended audience, and communicates accurately and effectively. Special considerations for health maps include ensuring confidentiality and reflecting the uncertainty of small area statistics. Statistical maps need to be based on sound practices and principles developed by the statistical and cartographic communities. Conclusion The biggest challenge is to ensure that maps of health statistics inform without misinforming. Advances in the sciences of cartography, statistics, and visualization of spatial data are constantly expanding the toolkit available to mapmakers to meet this challenge. Asking potential users to answer questions or to talk about what they see is
Advanced Mesh-Enabled Monte carlo capability for Multi-Physics Reactor Analysis
Wilson, Paul; Evans, Thomas; Tautges, Tim
2012-12-24
This project will accumulate high-precision fluxes throughout reactor geometry on a non- orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well
NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data.
Xia, Jianguo; Gill, Erin E; Hancock, Robert E W
2015-06-01
Meta-analysis of gene expression data sets is increasingly performed to help identify robust molecular signatures and to gain insights into underlying biological processes. The complicated nature of such analyses requires both advanced statistics and innovative visualization strategies to support efficient data comparison, interpretation and hypothesis generation. NetworkAnalyst (http://www.networkanalyst.ca) is a comprehensive web-based tool designed to allow bench researchers to perform various common and complex meta-analyses of gene expression data via an intuitive web interface. By coupling well-established statistical procedures with state-of-the-art data visualization techniques, NetworkAnalyst allows researchers to easily navigate large complex gene expression data sets to determine important features, patterns, functions and connections, thus leading to the generation of new biological hypotheses. This protocol provides a step-wise description of how to effectively use NetworkAnalyst to perform network analysis and visualization from gene lists; to perform meta-analysis on gene expression data while taking into account multiple metadata parameters; and, finally, to perform a meta-analysis of multiple gene expression data sets. NetworkAnalyst is designed to be accessible to biologists rather than to specialist bioinformaticians. The complete protocol can be executed in ∼1.5 h. Compared with other similar web-based tools, NetworkAnalyst offers a unique visual analytics experience that enables data analysis within the context of protein-protein interaction networks, heatmaps or chord diagrams. All of these analysis methods provide the user with supporting statistical and functional evidence.
Isolation and analysis of ginseng: advances and challenges
Wang, Chong-Zhi
2011-01-01
Ginseng occupies a prominent position in the list of best-selling natural products in the world. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support ginseng’s use worldwide. In the past decade, rapid development of technology has advanced many aspects of ginseng research. The aim of this review is to illustrate the recent advances in the isolation and analysis of ginseng, and to highlight their new applications and challenges. Emphasis is placed on recent trends and emerging techniques. The current article reviews the literature between January 2000 and September 2010. PMID:21258738
Issues affecting advanced passive light-water reactor safety analysis
Beelman, R.J.; Fletcher, C.D.; Modro, S.M.
1992-08-01
Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.
Issues affecting advanced passive light-water reactor safety analysis
Beelman, R.J.; Fletcher, C.D.; Modro, S.M.
1992-01-01
Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.
Advanced Post-Irradiation Examination Capabilities Alternatives Analysis Report
Jeff Bryan; Bill Landman; Porter Hill
2012-12-01
An alternatives analysis was performed for the Advanced Post-Irradiation Capabilities (APIEC) project in accordance with the U.S. Department of Energy (DOE) Order DOE O 413.3B, “Program and Project Management for the Acquisition of Capital Assets”. The Alternatives Analysis considered six major alternatives: ? No Action ? Modify Existing DOE Facilities – capabilities distributed among multiple locations ? Modify Existing DOE Facilities – capabilities consolidated at a few locations ? Construct New Facility ? Commercial Partnership ? International Partnerships Based on the alternatives analysis documented herein, it is recommended to DOE that the advanced post-irradiation examination capabilities be provided by a new facility constructed at the Materials and Fuels Complex at the Idaho National Laboratory.
NASA Astrophysics Data System (ADS)
Plaschke, F.; Glassmeier, K.-H.; Constantinescu, O. D.; Mann, I. R.; Milling, D. K.; Motschmann, U.; Rae, I. J.
2008-11-01
In this paper we introduce the field line resonance detector (FLRD), a wave telescope technique which has been specially adapted to estimate the spectral energy density of field line resonance (FLR) phase structures in a superposed wave field. The field line resonance detector is able to detect and correctly characterize several superposed FLR structures of a wave field and therefore constitutes a new and powerful tool in ULF pulsation studies. In our work we derive the technique from the classical wave telescope beamformer and present a statistical analysis of one year of ground based magnetometer data from the Canadian magnetometer network CANOPUS, now known as CARISMA. The statistical analysis shows that the FLRD is capable of detecting and characterizing superposed or hidden FLR structures in most of the detected ULF pulsation events; the one year statistical database is therefore extraordinarily comprehensive. The results of this analysis confirm the results of previous FLR characterizations and furthermore allow a detailed generalized dispersion analysis of FLRs.
Liu, Na; Li, Jun; Li, Bao-Guo
2014-11-01
The study of quality control of Chinese medicine has always been the hot and the difficulty spot of the development of traditional Chinese medicine (TCM), which is also one of the key problems restricting the modernization and internationalization of Chinese medicine. Multivariate statistical analysis is an analytical method which is suitable for the analysis of characteristics of TCM. It has been used widely in the study of quality control of TCM. Multivariate Statistical analysis was used for multivariate indicators and variables that appeared in the study of quality control and had certain correlation between each other, to find out the hidden law or the relationship between the data can be found,.which could apply to serve the decision-making and realize the effective quality evaluation of TCM. In this paper, the application of multivariate statistical analysis in the quality control of Chinese medicine was summarized, which could provided the basis for its further study. PMID:25775806
Application of multivariate statistical methods to the analysis of ancient Turkish potsherds
Martin, R.C.
1986-01-01
Three hundred ancient Turkish potsherds were analyzed by instrumental neutron activation analysis, and the resulting data analyzed by several techniques of multivariate statistical analysis, some only recently developed. The programs AGCLUS, MASLOC, and SIMCA were sequentially employed to characterize and group the samples by type of pottery and site of excavation. Comparison of the statistical analyses by each method provided archaeological insight into the site/type relationships of the samples and ultimately evidence relevant to the commercial relations between the ancient communities and specialization of pottery production over time. The techniques used for statistical analysis were found to be of significant potential utility in the future analysis of other archaeometric data sets. 25 refs., 33 figs.
Analysis of Variance with Summary Statistics in Microsoft® Excel®
ERIC Educational Resources Information Center
Larson, David A.; Hsu, Ko-Cheng
2010-01-01
Students regularly are asked to solve Single Factor Analysis of Variance problems given only the sample summary statistics (number of observations per category, category means, and corresponding category standard deviations). Most undergraduate students today use Excel for data analysis of this type. However, Excel, like all other statistical…
"ATLAS" Advanced Technology Life-cycle Analysis System
NASA Technical Reports Server (NTRS)
Lollar, Louis F.; Mankins, John C.; ONeil, Daniel A.
2004-01-01
Making good decisions concerning research and development portfolios-and concerning the best systems concepts to pursue - as early as possible in the life cycle of advanced technologies is a key goal of R&D management This goal depends upon the effective integration of information from a wide variety of sources as well as focused, high-level analyses intended to inform such decisions Life-cycle Analysis System (ATLAS) methodology and tool kit. ATLAS encompasses a wide range of methods and tools. A key foundation for ATLAS is the NASA-created Technology Readiness. The toolkit is largely spreadsheet based (as of August 2003). This product is being funded by the Human and Robotics The presentation provides a summary of the Advanced Technology Level (TRL) systems Technology Program Office, Office of Exploration Systems, NASA Headquarters, Washington D.C. and is being integrated by Dan O Neil of the Advanced Projects Office, NASA/MSFC, Huntsville, AL
Develop Advanced Nonlinear Signal Analysis Topographical Mapping System
NASA Technical Reports Server (NTRS)
Jong, Jen-Yi
1997-01-01
During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.
NASA Astrophysics Data System (ADS)
Li, Hongxin; Jiang, Haodong; Gao, Ming; Ma, Zhi; Ma, Chuangui; Wang, Wei
2015-12-01
The statistical fluctuation problem is a critical factor in all quantum key distribution (QKD) protocols under finite-key conditions. The current statistical fluctuation analysis is mainly based on independent random samples, however, the precondition cannot always be satisfied because of different choices of samples and actual parameters. As a result, proper statistical fluctuation methods are required to solve this problem. Taking the after-pulse contributions into consideration, this paper gives the expression for the secure key rate and the mathematical model for statistical fluctuations, focusing on a decoy-state QKD protocol [Z.-C. Wei et al., Sci. Rep. 3, 2453 (2013), 10.1038/srep02453] with a biased basis choice. On this basis, a classified analysis of statistical fluctuation is represented according to the mutual relationship between random samples. First, for independent identical relations, a deviation comparison is made between the law of large numbers and standard error analysis. Second, a sufficient condition is given that the Chernoff bound achieves a better result than Hoeffding's inequality based on only independent relations. Third, by constructing the proper martingale, a stringent way is proposed to deal issues based on dependent random samples through making use of Azuma's inequality. In numerical optimization, the impact on the secure key rate, the comparison of secure key rates, and the respective deviations under various kinds of statistical fluctuation analyses are depicted.
The linear statistical d.c. model of GaAs MESFET using factor analysis
NASA Astrophysics Data System (ADS)
Dobrzanski, Lech
1995-02-01
The linear statistical model of the GaAs MESFET's current generator is obtained by means of factor analysis. Three different MESFET deterministic models are taken into account in the analysis: the Statz model (ST), the Materka-type model (MT) and a new proprietary model of MESFET with implanted channel (PLD). It is shown that statistical models obtained using factor analysis provide excellent generation of the multidimensional random variable representing the drain current of MESFET. The method of implementation of the statistical model into the SPICE program is presented. It is proved that for a strongly limited number of Monte Carlo analysis runs in that program, the statistical models considered in each case (ST, MT and PLD) enable good reconstruction of the empirical factor structure. The empirical correlation matrix of model parameters is not reconstructed exactly by statistical modelling, but values of correlation matrix elements obtained from simulated data are within the confidence intervals for the small sample. This paper proves that a formal approach to statistical modelling using factor analysis is the right path to follow, in spite of the fact, that CAD systems (PSpice[MicroSim Corp.], Microwave Harmonica[Compact Software]) are not designed properly for generation of the multidimensional random variable. It is obvious that further progress in implementation of statistical methods in CAD software is required. Furthermore, a new approach to the MESFET's d.c. model is presented. The separate functions, describing the linear as well as the saturated region of MESFET output characteristics, are combined in the single equation. This way of modelling is particularly suitable for transistors with an implanted channel.
Numerical analysis of the V-Y shaped advancement flap.
Remache, D; Chambert, J; Pauchot, J; Jacquet, E
2015-10-01
The V-Y advancement flap is a usual technique for the closure of skin defects. A triangular flap is incised adjacent to a skin defect of rectangular shape. As the flap is advanced to close the initial defect, two smaller defects in the shape of a parallelogram are formed with respect to a reflection symmetry. The height of the defects depends on the apex angle of the flap and the closure efforts are related to the defects height. Andrades et al. 2005 have performed a geometrical analysis of the V-Y flap technique in order to reach a compromise between the flap size and the defects width. However, the geometrical approach does not consider the mechanical properties of the skin. The present analysis based on the finite element method is proposed as a complement to the geometrical one. This analysis aims to highlight the major role of the skin elasticity for a full analysis of the V-Y advancement flap. Furthermore, the study of this technique shows that closing at the flap apex seems mechanically the most interesting step. Thus different strategies of defect closure at the flap apex stemming from surgeon's know-how have been tested by numerical simulations. PMID:26342442
NASA Technical Reports Server (NTRS)
Dominick, Wayne D. (Editor); Bassari, Jinous; Triantafyllopoulos, Spiros
1984-01-01
The University of Southwestern Louisiana (USL) NASA PC R and D statistical analysis support package is designed to be a three-level package to allow statistical analysis for a variety of applications within the USL Data Base Management System (DBMS) contract work. The design addresses usage of the statistical facilities as a library package, as an interactive statistical analysis system, and as a batch processing package.
A longitudinal functional analysis framework for analysis of white matter tract statistics.
Yuan, Ying; Gilmore, John H; Geng, Xiujuan; Styner, Martin A; Chen, Kehui; Wang, Jane-Ling; Zhu, Hongtu
2013-01-01
Many longitudinal imaging studies have been/are being widely conducted to use diffusion tensor imaging (DTI) to better understand white matter maturation in normal controls and diseased subjects. There is an urgent demand for the development of statistical methods for analyzing diffusion properties along major fiber tracts obtained from longitudinal DTI studies. Jointly analyzing fiber-tract diffusion properties and covariates from longitudinal studies raises several major challenges including (i) infinite-dimensional functional response data, (ii) complex spatial-temporal correlation structure, and (iii) complex spatial smoothness. To address these challenges, this article is to develop a longitudinal functional analysis framework (LFAF) to delineate the dynamic changes of diffusion properties along major fiber tracts and their association with a set of covariates of interest (e.g., age and group status) and the structure of the variability of these white matter tract properties in various longitudinal studies. Our LFAF consists of a functional mixed effects model for addressing all three challenges, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial-temporal correlation structure, a test procedure with a global test statistic for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of LFAF and to demonstrate that LFAF significantly outperforms a voxel-wise mixed model method. We apply LFAF to study the spatial-temporal dynamics of white-matter fiber tracts in a clinical study of neurodevelopment.
Lee, L.; Helsel, D.
2005-01-01
Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.
Advances in Mid-Infrared Spectroscopy for Chemical Analysis
NASA Astrophysics Data System (ADS)
Haas, Julian; Mizaikoff, Boris
2016-06-01
Infrared spectroscopy in the 3–20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.
Advances in Mid-Infrared Spectroscopy for Chemical Analysis.
Haas, Julian; Mizaikoff, Boris
2016-06-12
Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.
Advances in Mid-Infrared Spectroscopy for Chemical Analysis
NASA Astrophysics Data System (ADS)
Haas, Julian; Mizaikoff, Boris
2016-06-01
Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.
Advances in urinary proteome analysis and biomarker discovery.
Fliser, Danilo; Novak, Jan; Thongboonkerd, Visith; Argilés, Angel; Jankowski, Vera; Girolami, Mark A; Jankowski, Joachim; Mischak, Harald
2007-04-01
Noninvasive diagnosis of kidney diseases and assessment of the prognosis are still challenges in clinical nephrology. Definition of biomarkers on the basis of proteome analysis, especially of the urine, has advanced recently and may provide new tools to solve those challenges. This article highlights the most promising technological approaches toward deciphering the human proteome and applications of the knowledge in clinical nephrology, with emphasis on the urinary proteome. The data in the current literature indicate that although a thorough investigation of the entire urinary proteome is still a distant goal, clinical applications are already available. Progress in the analysis of human proteome in health and disease will depend more on the standardization of data and availability of suitable bioinformatics and software solutions than on new technological advances. It is predicted that proteomics will play an important role in clinical nephrology in the very near future and that this progress will require interactive dialogue and collaboration between clinicians and analytical specialists.
Advanced gamma ray balloon experiment ground checkout and data analysis
NASA Technical Reports Server (NTRS)
Blackstone, M.
1976-01-01
A software programming package to be used in the ground checkout and handling of data from the advanced gamma ray balloon experiment is described. The Operator's Manual permits someone unfamiliar with the inner workings of the software system (called LEO) to operate on the experimental data as it comes from the Pulse Code Modulation interface, converting it to a form for later analysis, and monitoring the program of an experiment. A Programmer's Manual is included.
Advanced image analysis for the preservation of cultural heritage
NASA Astrophysics Data System (ADS)
France, Fenella G.; Christens-Barry, William; Toth, Michael B.; Boydston, Kenneth
2010-02-01
The Library of Congress' Preservation Research and Testing Division has established an advanced preservation studies scientific program for research and analysis of the diverse range of cultural heritage objects in its collection. Using this system, the Library is currently developing specialized integrated research methodologies for extending preservation analytical capacities through non-destructive hyperspectral imaging of cultural objects. The research program has revealed key information to support preservation specialists, scholars and other institutions. The approach requires close and ongoing collaboration between a range of scientific and cultural heritage personnel - imaging and preservation scientists, art historians, curators, conservators and technology analysts. A research project of the Pierre L'Enfant Plan of Washington DC, 1791 had been undertaken to implement and advance the image analysis capabilities of the imaging system. Innovative imaging options and analysis techniques allow greater processing and analysis capacities to establish the imaging technique as the first initial non-invasive analysis and documentation step in all cultural heritage analyses. Mapping spectral responses, organic and inorganic data, topography semi-microscopic imaging, and creating full spectrum images have greatly extended this capacity from a simple image capture technique. Linking hyperspectral data with other non-destructive analyses has further enhanced the research potential of this image analysis technique.
Advanced superposition methods for high speed turbopump vibration analysis
NASA Technical Reports Server (NTRS)
Nielson, C. E.; Campany, A. D.
1981-01-01
The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.
New ordering principle for the classical statistical analysis of Poisson processes with background
NASA Astrophysics Data System (ADS)
Giunti, C.
1999-03-01
Inspired by the recent proposal by Feldman and Cousins of a ``unified approach to the classical statistical analysis of small signals'' based on a choice of ordering in Neyman's construction of classical confidence intervals, I propose a new ordering principle for the classical statistical analysis of Poisson processes with a background which minimizes the effect on the resulting confidence intervals of the observation of fewer background events than expected. The new ordering principle is applied to the calculation of the confidence region implied by the recent null result of the KARMEN neutrino oscillation experiment.
Huang, Huei-Chung; Niu, Yi; Qin, Li-Xuan
2015-01-01
Deep sequencing has recently emerged as a powerful alternative to microarrays for the high-throughput profiling of gene expression. In order to account for the discrete nature of RNA sequencing data, new statistical methods and computational tools have been developed for the analysis of differential expression to identify genes that are relevant to a disease such as cancer. In this paper, it is thus timely to provide an overview of these analysis methods and tools. For readers with statistical background, we also review the parameter estimation algorithms and hypothesis testing strategies used in these methods. PMID:26688660
Ribes, Delphine; Parafita, Julia; Charrier, Rémi; Magara, Fulvio; Magistretti, Pierre J; Thiran, Jean-Philippe
2010-11-23
In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.
A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.
Lin, Johnny; Bentler, Peter M
2012-01-01
Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.
Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis.
Obeid, Rita; Brooks, Patricia J; Powers, Kasey L; Gillespie-Lynch, Kristen; Lum, Jarrad A G
2016-01-01
Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI) and Autism Spectrum Disorder (ASD). Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons) and ASD (13 studies, 20 comparisons) to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, and Probabilistic Classification). Individuals with SLI showed deficits in statistical learning relative to age-matched controls. In contrast, statistical learning was intact in individuals with ASD relative to controls. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman and Pierpont, 2005), impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD.
Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis
Obeid, Rita; Brooks, Patricia J.; Powers, Kasey L.; Gillespie-Lynch, Kristen; Lum, Jarrad A. G.
2016-01-01
Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI) and Autism Spectrum Disorder (ASD). Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons) and ASD (13 studies, 20 comparisons) to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, and Probabilistic Classification). Individuals with SLI showed deficits in statistical learning relative to age-matched controls. In contrast, statistical learning was intact in individuals with ASD relative to controls. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman and Pierpont, 2005), impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD. PMID:27602006
Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis.
Obeid, Rita; Brooks, Patricia J; Powers, Kasey L; Gillespie-Lynch, Kristen; Lum, Jarrad A G
2016-01-01
Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI) and Autism Spectrum Disorder (ASD). Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons) and ASD (13 studies, 20 comparisons) to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, and Probabilistic Classification). Individuals with SLI showed deficits in statistical learning relative to age-matched controls. In contrast, statistical learning was intact in individuals with ASD relative to controls. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman and Pierpont, 2005), impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD. PMID:27602006
Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis
Obeid, Rita; Brooks, Patricia J.; Powers, Kasey L.; Gillespie-Lynch, Kristen; Lum, Jarrad A. G.
2016-01-01
Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI) and Autism Spectrum Disorder (ASD). Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons) and ASD (13 studies, 20 comparisons) to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, and Probabilistic Classification). Individuals with SLI showed deficits in statistical learning relative to age-matched controls. In contrast, statistical learning was intact in individuals with ASD relative to controls. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman and Pierpont, 2005), impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD.
Long-term Statistical Analysis of the Simultaneity of Forbush Decrease Events at Middle Latitudes
NASA Astrophysics Data System (ADS)
Lee, Seongsuk; Oh, Suyeon; Yi, Yu; Evenson, Paul; Jee, Geonhwa; Choi, Hwajin
2015-03-01
Forbush Decreases (FD) are transient, sudden reductions of cosmic ray (CR) intensity lasting a few days, to a week. Such events are observed globally using ground neutron monitors (NMs). Most studies of FD events indicate that an FD event is observed simultaneously at NM stations located all over the Earth. However, using statistical analysis, previous researchers verified that while FD events could occur simultaneously, in some cases, FD events could occur non-simultaneously. Previous studies confirmed the statistical reality of non-simultaneous FD events and the mechanism by which they occur, using data from high-latitude and middle-latitude NM stations. In this study, we used long-term data (1971-2006) from middle-latitude NM stations (Irkutsk, Climax, and Jungfraujoch) to enhance statistical reliability. According to the results from this analysis, the variation of cosmic ray intensity during the main phase, is larger (statistically significant) for simultaneous FD events, than for non-simultaneous ones. Moreover, the distribution of main-phase-onset time shows differences that are statistically significant. While the onset times for the simultaneous FDs are distributed evenly over 24- hour intervals (day and night), those of non-simultaneous FDs are mostly distributed over 12-hour intervals, in daytime. Thus, the existence of the two kinds of FD events, according to differences in their statistical properties, were verified based on data from middle-latitude NM stations.
Gene set analysis for GWAS: assessing the use of modified Kolmogorov-Smirnov statistics.
Debrabant, Birgit; Soerensen, Mette
2014-10-01
We discuss the use of modified Kolmogorov-Smirnov (KS) statistics in the context of gene set analysis and review corresponding null and alternative hypotheses. Especially, we show that, when enhancing the impact of highly significant genes in the calculation of the test statistic, the corresponding test can be considered to infer the classical self-contained null hypothesis. We use simulations to estimate the power for different kinds of alternatives, and to assess the impact of the weight parameter of the modified KS statistic on the power. Finally, we show the analogy between the weight parameter and the genesis and distribution of the gene-level statistics, and illustrate the effects of differential weighting in a real-life example.
Advanced stress analysis methods applicable to turbine engine structures
NASA Technical Reports Server (NTRS)
Pian, Theodore H. H.
1991-01-01
The following tasks on the study of advanced stress analysis methods applicable to turbine engine structures are described: (1) constructions of special elements which contain traction-free circular boundaries; (2) formulation of new version of mixed variational principles and new version of hybrid stress elements; (3) establishment of methods for suppression of kinematic deformation modes; (4) construction of semiLoof plate and shell elements by assumed stress hybrid method; and (5) elastic-plastic analysis by viscoplasticity theory using the mechanical subelement model.
Advances in Computational Stability Analysis of Composite Aerospace Structures
Degenhardt, R.; Araujo, F. C. de
2010-09-30
European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.
Advanced Models for Aeroelastic Analysis of Propulsion Systems
NASA Technical Reports Server (NTRS)
Keith, Theo G., Jr.; Mahajan, Aparajit
1996-01-01
This report describes an integrated, multidisciplinary simulation capability for aeroelastic analysis and optimization of advanced propulsion systems. This research is intended to improve engine development, acquisition, and maintenance costs. One of the proposed simulations is aeroelasticity of blades, cowls, and struts in an ultra-high bypass fan. These ducted fans are expected to have significant performance, fuel, and noise improvements over existing engines. An interface program was written to use modal information from COBSTAN and NASTRAN blade models in aeroelastic analysis with a single rotation ducted fan aerodynamic code.
Subramanyam, Busetty; Das, Ashutosh
2014-01-01
In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878
NASA Astrophysics Data System (ADS)
Oliveira Mendes, Thiago de; Pinto, Liliane Pereira; Santos, Laurita dos; Tippavajhala, Vamshi Krishna; Téllez Soto, Claudio Alberto; Martin, Airton Abrahão
2016-07-01
The analysis of biological systems by spectroscopic techniques involves the evaluation of hundreds to thousands of variables. Hence, different statistical approaches are used to elucidate regions that discriminate classes of samples and to propose new vibrational markers for explaining various phenomena like disease monitoring, mechanisms of action of drugs, food, and so on. However, the technical statistics are not always widely discussed in applied sciences. In this context, this work presents a detailed discussion including the various steps necessary for proper statistical analysis. It includes univariate parametric and nonparametric tests, as well as multivariate unsupervised and supervised approaches. The main objective of this study is to promote proper understanding of the application of various statistical tools in these spectroscopic methods used for the analysis of biological samples. The discussion of these methods is performed on a set of in vivo confocal Raman spectra of human skin analysis that aims to identify skin aging markers. In the Appendix, a complete routine of data analysis is executed in a free software that can be used by the scientific community involved in these studies.
Validation Database Based Thermal Analysis of an Advanced RPS Concept
NASA Technical Reports Server (NTRS)
Balint, Tibor S.; Emis, Nickolas D.
2006-01-01
Advanced RPS concepts can be conceived, designed and assessed using high-end computational analysis tools. These predictions may provide an initial insight into the potential performance of these models, but verification and validation are necessary and required steps to gain confidence in the numerical analysis results. This paper discusses the findings from a numerical validation exercise for a small advanced RPS concept, based on a thermal analysis methodology developed at JPL and on a validation database obtained from experiments performed at Oregon State University. Both the numerical and experimental configurations utilized a single GPHS module enabled design, resembling a Mod-RTG concept. The analysis focused on operating and environmental conditions during the storage phase only. This validation exercise helped to refine key thermal analysis and modeling parameters, such as heat transfer coefficients, and conductivity and radiation heat transfer values. Improved understanding of the Mod-RTG concept through validation of the thermal model allows for future improvements to this power system concept.
Structural Configuration Systems Analysis for Advanced Aircraft Fuselage Concepts
NASA Technical Reports Server (NTRS)
Mukhopadhyay, Vivek; Welstead, Jason R.; Quinlan, Jesse R.; Guynn, Mark D.
2016-01-01
Structural configuration analysis of an advanced aircraft fuselage concept is investigated. This concept is characterized by a double-bubble section fuselage with rear mounted engines. Based on lessons learned from structural systems analysis of unconventional aircraft, high-fidelity finite-element models (FEM) are developed for evaluating structural performance of three double-bubble section configurations. Structural sizing and stress analysis are applied for design improvement and weight reduction. Among the three double-bubble configurations, the double-D cross-section fuselage design was found to have a relatively lower structural weight. The structural FEM weights of these three double-bubble fuselage section concepts are also compared with several cylindrical fuselage models. Since these fuselage concepts are different in size, shape and material, the fuselage structural FEM weights are normalized by the corresponding passenger floor area for a relative comparison. This structural systems analysis indicates that an advanced composite double-D section fuselage may have a relative structural weight ratio advantage over a conventional aluminum fuselage. Ten commercial and conceptual aircraft fuselage structural weight estimates, which are empirically derived from the corresponding maximum takeoff gross weight, are also presented and compared with the FEM- based estimates for possible correlation. A conceptual full vehicle FEM model with a double-D fuselage is also developed for preliminary structural analysis and weight estimation.
Advanced analysis of case histories as a mean for improved plant availability
Jovanovic, A.S.; Poloni, M.; Kautz, H.R.
1996-12-31
The paper presents the novel idea of using large collections of case histories for supporting operation and maintenance of power plants. Large systems for storage and management of case histories (operational problems, failures, inspection reports, etc.) have been developed at MPA Stuttgart. Their development has been supported, in terms of supplying data and providing suitable test bed, by GKM. Besides the data management and conventional statistical analysis, the systems are being upgraded nowadays with advanced intelligent analysis modules. These modules allow (e.g.) to select a subset of relevant case studies and to analyze possible trends and dependencies, both quantitative and qualitative, in the subset. For a new case, a subset of similar cases can be found and analyzed. The results of the analysis can then be used either for the diagnosis of possible problems or for assessment of risks in the given new case.
Statistical Analysis of CFD Solutions from the Fourth AIAA Drag Prediction Workshop
NASA Technical Reports Server (NTRS)
Morrison, Joseph H.
2010-01-01
A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from the U.S., Europe, Asia, and Russia using a variety of grid systems and turbulence models for the June 2009 4th Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was a new subsonic transport model, the Common Research Model, designed using a modern approach for the wing and included a horizontal tail. The fourth workshop focused on the prediction of both absolute and incremental drag levels for wing-body and wing-body-horizontal tail configurations. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with earlier workshops using the statistical framework.
Landing Site Dispersion Analysis and Statistical Assessment for the Mars Phoenix Lander
NASA Technical Reports Server (NTRS)
Bonfiglio, Eugene P.; Adams, Douglas; Craig, Lynn; Spencer, David A.; Strauss, William; Seelos, Frank P.; Seelos, Kimberly D.; Arvidson, Ray; Heet, Tabatha
2008-01-01
The Mars Phoenix Lander launched on August 4, 2007 and successfully landed on Mars 10 months later on May 25, 2008. Landing ellipse predicts and hazard maps were key in selecting safe surface targets for Phoenix. Hazard maps were based on terrain slopes, geomorphology maps and automated rock counts of MRO's High Resolution Imaging Science Experiment (HiRISE) images. The expected landing dispersion which led to the selection of Phoenix's surface target is discussed as well as the actual landing dispersion predicts determined during operations in the weeks, days, and hours before landing. A statistical assessment of these dispersions is performed, comparing the actual landing-safety probabilities to criteria levied by the project. Also discussed are applications for this statistical analysis which were used by the Phoenix project. These include using the statistical analysis used to verify the effectiveness of a pre-planned maneuver menu and calculating the probability of future maneuvers.
Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis
Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun
2014-01-01
As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687
NASA Technical Reports Server (NTRS)
Wolf, S. F.; Lipschutz, M. E.
1993-01-01
Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.
NASA Astrophysics Data System (ADS)
Bachmann, Michael
2013-05-01
The simulation of biomolecular structural transitions such as folding and aggregation does not only require adequate models that reflect the key aspects of the cooperative transition behaviour. It is likewise important to employ thermodynamically correct simulation methods and to perform an accurate subsequent statistical analysis of the data obtained in the simulation. The efficient combination of methodology and analysis can be quite sophisticated, but also very instructive in their feedback to a better understanding of the physics of the underlying cooperative processes that drive the conformational transition. We here show that the density of states, which is the central result of multicanonical sampling and any other generalized-ensemble simulation, serves as the optimal basis for the microcanonical statistical analysis of transitions. The microcanonical inflection-point analysis method, which has been introduced for this purpose recently, is a perfect tool for a precise, unique identification and classification of all structural transitions.
Exstatix: Expandable Statistical Analysis System for the Macintosh. A Software Review.
ERIC Educational Resources Information Center
Ferrell, Barbara G.
The Exstatix statistical analysis software package by K. C. Killion for use with Macintosh computers is evaluated. In evaluating the package, the framework developed by C. J. Ansorge et al. (1986) was used. This framework encompasses features such as transportability of files, compatibility of files with other Macintosh software, and ability to…
ERIC Educational Resources Information Center
Hendrix, Dean
2010-01-01
This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…
1977-78 Cost Analysis for Florida Schools and Districts. Statistical Report. Series 79-01.
ERIC Educational Resources Information Center
Florida State Dept. of Education, Tallahassee. Div. of Public Schools.
This statistical report describes some of the cost analysis information available from computer reports produced by the Florida Department of Education. It reproduces examples of Florida school and school district financial data that can be used by state, district, and school-level administrators as they analyze program costs and expenditures. The…
ERIC Educational Resources Information Center
Zhou, Ping; Wang, Qinwen; Yang, Jie; Li, Jingqiu; Guo, Junming; Gong, Zhaohui
2015-01-01
This study aimed to investigate the statuses on the publishing and usage of college biochemistry textbooks in China. A textbook database was constructed and the statistical analysis was adopted to evaluate the textbooks. The results showed that there were 945 (~57%) books for theory teaching, 379 (~23%) books for experiment teaching and 331 (~20%)…
Indexing Combined with Statistical Deflation as a Tool for Analysis of Longitudinal Data.
ERIC Educational Resources Information Center
Babcock, Judith A.
Indexing is a tool that can be used with longitudinal, quantitative data for analysis of relative changes and for comparisons of changes among items. For greater accuracy, raw financial data should be deflated into constant dollars prior to indexing. This paper demonstrates the procedures for indexing, statistical deflation, and the use of…
ERIC Educational Resources Information Center
Lau, Joann M.; Korn, Robert W.
2007-01-01
In this article, the authors present a laboratory exercise in data collection and statistical analysis in biological space using clustered stomates on leaves of "Begonia" plants. The exercise can be done in middle school classes by students making their own slides and seeing imprints of cells, or at the high school level through collecting data of…
Bayesian Statistical Analysis Applied to NAA Data for Neutron Flux Spectrum Determination
NASA Astrophysics Data System (ADS)
Chiesa, D.; Previtali, E.; Sisti, M.
2014-04-01
In this paper, we present a statistical method, based on Bayesian statistics, to evaluate the neutron flux spectrum from the activation data of different isotopes. The experimental data were acquired during a neutron activation analysis (NAA) experiment [A. Borio di Tigliole et al., Absolute flux measurement by NAA at the Pavia University TRIGA Mark II reactor facilities, ENC 2012 - Transactions Research Reactors, ISBN 978-92-95064-14-0, 22 (2012)] performed at the TRIGA Mark II reactor of Pavia University (Italy). In order to evaluate the neutron flux spectrum, subdivided in energy groups, we must solve a system of linear equations containing the grouped cross sections and the activation rate data. We solve this problem with Bayesian statistical analysis, including the uncertainties of the coefficients and the a priori information about the neutron flux. A program for the analysis of Bayesian hierarchical models, based on Markov Chain Monte Carlo (MCMC) simulations, is used to define the problem statistical model and solve it. The energy group fluxes and their uncertainties are then determined with great accuracy and the correlations between the groups are analyzed. Finally, the dependence of the results on the prior distribution choice and on the group cross section data is investigated to confirm the reliability of the analysis.
Development of Statistically Parallel Tests by Analysis of Unique Item Variance.
ERIC Educational Resources Information Center
Ree, Malcolm James
A method for developing statistically parallel tests based on the analysis of unique item variance was developed. A test population of 907 basic airmen trainees were required to estimate the angle at which an object in a photograph was viewed, selecting from eight possibilities. A FORTRAN program known as VARSEL was used to rank all the test items…