Statistical Data Analysis in the Computer Age
NASA Astrophysics Data System (ADS)
Efron, Bradley; Tibshirani, Robert
1991-07-01
Most of our familiar statistical methods, such as hypothesis testing, linear regression, analysis of variance, and maximum likelihood estimation, were designed to be implemented on mechanical calculators. modern electronic computation has encouraged a host of new statistical methods that require fewer distributional assumptions than their predecessors and can be applied to more complicated statistical estimators. These methods allow the scientist to explore and describe data and draw valid statistical inferences without the usual concerns for mathematical tractability. This is possible because traditional methods of mathematical analysis are replaced by specially constructed computer algorithms. Mathematics has not disappeared from statistical theory. It is the main method for deciding which algorithms are correct and efficient tools for automating statistical inference.
Statistical analysis of accelerated temperature aging of semiconductor devices
NASA Astrophysics Data System (ADS)
Johnson, W. A.; Milles, M. F.
1981-05-01
A number of semiconductor devices taken from a distribution were operated at several elevated temperatures to induce failure in all devices within a reasonable time. Assuming general characteristics of the device failure probability density function (pdf) and its temperature dependence, the expected cumulative failure function (cff) for devices in normal operation were estimated based on statistical inference, taking the average probability of a random device (from the same distribution but operated at a normal temperature) failing as a function of time. A review of the mathematical formalism employed in semiconductor reliability discussions is included. Three failure pdf's at particular usefulness to this analysis--exponential, normal, and lognormal - are discussed. The cff, at times orders of magnitude loss then, at times comparable to the desired system useful, life (*10 to the 4th power to 10 to the 5th power hr) is considered. A review of accelerated temperature aging is presented, and the assumption concerning the general characteristics of the failure pdf, which are fundamental to this analysis, are emphasized.
NASA Technical Reports Server (NTRS)
Baker, K. B.; Sturrock, P. A.
1975-01-01
The question of whether pulsars form a single group or whether pulsars come in two or more different groups is discussed. It is proposed that such groups might be related to several factors such as the initial creation of the neutron star, or the orientation of the magnetic field axis with the spin axis. Various statistical models are examined.
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.
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 Energy Analysis Program
NASA Technical Reports Server (NTRS)
Ferebee, R. C.; Trudell, R. W.; Yano, L. I.; Nygaard, S. I.
1985-01-01
Statistical Energy Analysis (SEA) is powerful tool for estimating highfrequency vibration spectra of complex structural systems and incorporated into computer program. Basic SEA analysis procedure divided into three steps: Idealization, parameter generation, and problem solution. SEA computer program written in FORTRAN V for batch execution.
Eshima, Nobuoki; Tokumaru, Osamu; Hara, Shohei; Bacal, Kira; Korematsu, Seigo; Karukaya, Shigeru; Uruma, Kiyo; Okabe, Nobuhiko; Matsuishi, Toyojiro
2012-01-01
Background To prevent and control infectious diseases, it is important to understand how sex and age influence morbidity rates, but consistent clear descriptions of differences in the reported incidence of infectious diseases in terms of sex and age are sparse. Methods and Findings Data from the Japanese surveillance system for infectious diseases from 2000 to 2009 were used in the analysis of seven viral and four bacterial infectious diseases with relatively large impact on the Japanese community. The male-to-female morbidity (MFM) ratios in different age groups were estimated to compare incidence rates of symptomatic reported infection between the sexes at different ages. MFM ratios were >1 for five viral infections out of seven in childhood, i.e. male children were more frequently reported as infected than females with pharyngoconjunctival fever, herpangina, hand-foot-and-mouth disease, mumps, and varicella. More males were also reported to be infected with erythema infectiosum and exanthema subitum, but only in children 1 year of age. By contrast, in adulthood the MFM ratios decreased to <1 for all of the viral infections above except varicella, i.e. adult women were more frequently reported to be infected than men. Sex- and age-related differences in reported morbidity were also documented for bacterial infections. Reported morbidity for enterohemorrhagic Escherichia coli infection was higher in adult females and females were reportedly more infected with mycoplasma pneumonia than males in all age groups up to 70 years. Conclusions Sex-related differences in reported morbidity for viral and bacterial infections were documented among different age groups. Changes in MFM ratios with age may reflect differences between the sexes in underlying development processes, including those affecting the immune, endocrine, and reproductive systems, or differences in reporting rates. PMID:22848753
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.
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.
Statistical Approaches for the Study of Cognitive and Brain Aging
Chen, Huaihou; Zhao, Bingxin; Cao, Guanqun; Proges, Eric C.; O'Shea, Andrew; Woods, Adam J.; Cohen, Ronald A.
2016-01-01
Neuroimaging studies of cognitive and brain aging often yield massive datasets that create many analytic and statistical challenges. In this paper, we discuss and address several limitations in the existing work. (1) Linear models are often used to model the age effects on neuroimaging markers, which may be inadequate in capturing the potential nonlinear age effects. (2) Marginal correlations are often used in brain network analysis, which are not efficient in characterizing a complex brain network. (3) Due to the challenge of high-dimensionality, only a small subset of the regional neuroimaging markers is considered in a prediction model, which could miss important regional markers. To overcome those obstacles, we introduce several advanced statistical methods for analyzing data from cognitive and brain aging studies. Specifically, we introduce semiparametric models for modeling age effects, graphical models for brain network analysis, and penalized regression methods for selecting the most important markers in predicting cognitive outcomes. We illustrate these methods using the healthy aging data from the Active Brain Study. PMID:27486400
Analysis of network statistics
NASA Astrophysics Data System (ADS)
Cottrell, R. L. A.
1987-08-01
This talk discusses the types and sources of data obtainable from networks of computer systems and terminals connected by communications paths. These paths often utilize mixtures of protocols and devices (such as modems, multiplexors, switches and front-ends) from multiple vendors. The talk describes how the data can be gathered from these devices and protocol layers, consolidated, stored, and analyzed. The analysis typically includes merging information from data bases describing the network topology, components, etc. Examples of reports and displays of the information gleaned are shown, together with illustrations of how the information may be useful for troubleshooting, performance measurement, auditing, accounting, and trend prediction.
STATISTICAL SAMPLING AND DATA ANALYSIS
Research is being conducted to develop approaches to improve soil and sediment sampling techniques, measurement design and geostatistics, and data analysis via chemometric, environmetric, and robust statistical methods. Improvements in sampling contaminated soil and other hetero...
Federal Interagency Forum on Aging-Related Statistics
Member Agencies Federal Agency Login X Administration on Aging Agency for Healthcare Research and Quality Bureau of ... National Center for Health Statistics National Institute on Aging Office of the Assistant Secretary for Planning & Evaluation, ...
Statistical physics of age related macular degeneration
NASA Astrophysics Data System (ADS)
Family, Fereydoon; Mazzitello, K. I.; Arizmendi, C. M.; Grossniklaus, H. E.
Age-related macular degeneration (AMD) is the leading cause of blindness beyond the age of 50 years. The most common pathogenic mechanism that leads to AMD is choroidal neovascularization (CNV). CNV is produced by accumulation of residual material caused by aging of retinal pigment epithelium cells (RPE). The RPE is a phagocytic system that is essential for renewal of photoreceptors (rods and cones). With time, incompletely degraded membrane material builds up in the form of lipofuscin. Lipofuscin is made of free-radical-damaged protein and fat, which forms not only in AMD, but also Alzheimer disease and Parkinson disease. The study of lipofuscin formation and growth is important, because of their association with cellular aging. We introduce a model of non-equilibrium cluster growth and aggregation that we have developed for studying the formation and growth of lipofuscin in the aging RPE. Our results agree with a linear growth of the number of lipofuscin granules with age. We apply the dynamic scaling approach to our model and find excellent data collapse for the cluster size distribution. An unusual feature of our model is that while small particles are removed from the RPE the larger ones become fixed and grow by aggregation.
STATISTICS AND DATA ANALYSIS WORKSHOP
On Janauary 15 and 16, 2003, a workshop for Tribal water resources staff on Statistics and Data Analysis was held at the Indian Springs Lodge on the Forest County Potowatomi Reservation near Wabeno, WI. The workshop was co-sponsored by the EPA, Sokaogon Chippewa (Mole Lake) Comm...
Statistical Analysis in Climate Research
NASA Astrophysics Data System (ADS)
von Storch, Hans; Zwiers, Francis W.
2002-03-01
The purpose of this book is to help the climatologist understand the basic precepts of the statistician's art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialized techniques used specifically by climatologists are all contained within this one source. There are a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research.
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.
Performance of statistical energy analysis
NASA Technical Reports Server (NTRS)
Davis, R. F.; Hines, D. E.
1973-01-01
Statistical energy analysis (SEA) methods have been developed for high frequency modal analyses on random vibration environments. These SEA methods are evaluated by comparing analytical predictions to test results. Simple test methods are developed for establishing SEA parameter values. Techniques are presented, based on the comparison of the predictions with test values, for estimating SEA accuracy as a function of frequency for a general structure.
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
Statistical analysis of nucleotide sequences.
Stückle, E E; Emmrich, C; Grob, U; Nielsen, P J
1990-01-01
In order to scan nucleic acid databases for potentially relevant but as yet unknown signals, we have developed an improved statistical model for pattern analysis of nucleic acid sequences by modifying previous methods based on Markov chains. We demonstrate the importance of selecting the appropriate parameters in order for the method to function at all. The model allows the simultaneous analysis of several short sequences with unequal base frequencies and Markov order k not equal to 0 as is usually the case in databases. As a test of these modifications, we show that in E. coli sequences there is a bias against palindromic hexamers which correspond to known restriction enzyme recognition sites. PMID:2251125
Statistical analysis of pyroshock data
NASA Astrophysics Data System (ADS)
Hughes, William O.
2002-05-01
The sample size of aerospace pyroshock test data is typically small. This often forces the engineer to make assumptions on its population distribution and to use conservative margins or methodologies in determining shock specifications. For example, the maximum expected environment is often derived by adding 3-6 dB to the maximum envelope of a limited amount of shock data. The recent availability of a large amount of pyroshock test data has allowed a rare statistical analysis to be performed. Findings and procedures from this analysis will be explained, including information on population distributions, procedures to properly combine families of test data, and methods of deriving appropriate shock specifications for a multipoint shock source.
Statistical Design in Isothermal Aging of Polyimide Resins
NASA Technical Reports Server (NTRS)
Sutter, James K.; Jobe, Marcus; Crane, Elizabeth A.
1995-01-01
Recent developments in research on polyimides for high temperature applications have led to the synthesis of many new polymers. Among the criteria that determines their thermal oxidative stability, isothermal aging is one of the most important. Isothermal aging studies require that many experimental factors are controlled to provide accurate results. In this article we describe a statistical plan that compares the isothermal stability of several polyimide resins, while minimizing the variations inherent in high-temperature aging studies.
Statistical Handbook on Aging Americans. 1994 Edition. Statistical Handbook Series Number 5.
ERIC Educational Resources Information Center
Schick, Frank L., Ed.; Schick, Renee, Ed.
This statistical handbook contains 378 tables and charts illustrating the changes in the United States' aging population based on data collected during the 1990 census and several other surveys. The tables and charts are organized by topic as follows: demographics (age and sex distribution, life expectancy, race and ethnicity, geographic…
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.
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.
Fake Statistically Valid Isotopic Ages in Impact Crater Geochronology
NASA Astrophysics Data System (ADS)
Jourdan, F.; Schmieder, M.; McWilliams, M. M.; Buchner, E.
2009-05-01
Precise dating of impact structures is crucial in several fundamental aspects, such as correlating effects on the bio- and geosphere caused by these catastrophic processes. Among the 176 listed impact structures [1], only 25 have a stated age precision better than ± 2%. Statistical investigation of these 25 ages showed that 11 ages are accurate, 12 are at best ambiguous, and 2 are not well characterized [2]. In this study, we show that even with statistically valid isotope ages, the age of an impact can be "missed" by several hundred millions of years. We present a new 40Ar/39Ar plateau age of 444 ± 4 Ma for the Acraman structure (real age ˜590 Ma [3]) and four plateau ages ranging from 81.07 ± 0.76 Ma to 74.6 ± 1.5 Ma for the Brent structure (estimated real age ˜453 Ma [4]). In addition, we discuss a 40Ar/39Ar plateau age of 994 ± 11, recently obtained by [5] on the Dhala structure (real age ˜2.0 Ga [5]). Despite careful sample preparations (single grain handpicking and HF leaching, in order to remove alteration phases), these results are much younger than the impact ages. Petrographic observations show that Acraman and Dhala grain separates all have an orange color and show evidence of alteration. This suggests that these ages are the results of hydrothermal events that triggered intensive 40Ar* loss and crystallization of secondary phases. More intriguing are the Brent samples (glassy melt rocks obtained from a drill core) that appeared very fresh under the microscope. The Brent glass might be a Cretaceous pseudotachylite generated by a late adjustment of the structure and/or by a local earthquake. Because we know the approximate age of the craters with stratigraphic evidences, these outliers are easy to identify. However, this is a red flag for any uncritical interpretation of isotopic ages (including e.g., 40Ar/39Ar, U/Pb, or U-Th/He [6]). In this paper, we encourage a multi-technique approach (i.e., isotopic, stratigraphic, paleogeographic [7,8]) and
Statistical estimation of mineral age by K-Ar method
Vistelius, A.B.; Drubetzkoy, E.R.; Faas, A.V. )
1989-11-01
Statistical estimation of age of {sup 40}Ar/{sup 40}K ratios may be considered a result of convolution of uniform and normal distributions with different weights for different minerals. Data from Gul'shad Massif (Nearbalkhash, Kazakhstan, USSR) indicate that {sup 40}Ar/{sup 40}K ratios reflecting the intensity of geochemical processes can be resolved using convolutions. Loss of {sup 40}Ar in biotites is shown whereas hornblende retained the original content of {sup 40}Ar throughout the geological history of the massif. Results demonstrate that different estimation methods must be used for different minerals and different rocks when radiometric ages are employed for dating.
Asymptotic modal analysis and statistical energy analysis
NASA Technical Reports Server (NTRS)
Dowell, Earl H.; Peretti, Linda F.
1990-01-01
The sound field of a structural-acoustic enclosure was subject to experimental analysis and theoretical description in order to develop an efficient and accurate method for predicting sound pressure levels in enclosures such as aircraft fuselages. Asymptotic Modal Analysis (AMA) is the method under investigation. AMA is derived from classical modal analysis (CMA) by considering the asymptotic limit of the sound pressure level as the number of acoustic and/or structural modes approaches infinity. Using AMA, results identical to those of Statistical Energy Analysis (SEA) were obtained for the spatially-averaged sound pressure levels in the interior. AMA is systematically derived from CMA and therefore the degree of generality of the end result can be adjusted through the choice of appropriate simplifying assumptions. For example, AMA can be used to obtain local sound pressure levels at particular points inside the enclosure, or to include the effects of varying the size and/or location of the sound source. AMA theoretical results were compared with CMA theory and also with experiment for the case where the structural-acoustic enclosure is a rectangular cavity with part of one wall flexible and vibrating, while the rest of the cavity is rigid.
Statistical analysis of barefoot impressions.
Kennedy, Robert B; Pressman, Irwin S; Chen, Sanping; Petersen, Peter H; Pressman, Ari E
2003-01-01
Comparison of the shapes of barefoot impressions from an individual with footprints or shoes linked to a crime may be useful as a means of including or excluding that individual as possibly being at the scene of a crime. The question of the distinguishability of a person's barefoot print arises frequently. This study indicates that measurements taken from the outlines of inked footprint impressions show a great degree of variability between donors and a great degree of similarity for multiple impressions taken from the same donor. The normality of the set of measurements on footprint outlines that we have selected for this study is confirmed. A statistical justification for the use of the product rule on individual statistical precisions is developed. PMID:12570199
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.
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.
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.
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…
Aging and the statistical learning of grammatical form classes.
Schwab, Jessica F; Schuler, Kathryn D; Stillman, Chelsea M; Newport, Elissa L; Howard, James H; Howard, Darlene V
2016-08-01
Language learners must place unfamiliar words into categories, often with few explicit indicators about when and how that word can be used grammatically. Reeder, Newport, and Aslin (2013) showed that college students can learn grammatical form classes from an artificial language by relying solely on distributional information (i.e., contextual cues in the input). Here, 2 experiments revealed that healthy older adults also show such statistical learning, though they are poorer than young at distinguishing grammatical from ungrammatical strings. This finding expands knowledge of which aspects of learning vary with aging, with potential implications for second language learning in late adulthood. (PsycINFO Database Record PMID:27294711
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…
Statistical Analysis of DWPF ARG-1 Data
Harris, S.P.
2001-03-02
A statistical analysis of analytical results for ARG-1, an Analytical Reference Glass, blanks, and the associated calibration and bench standards has been completed. These statistics provide a means for DWPF to review the performance of their laboratory as well as identify areas of improvement.
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 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.
STATISTICAL ANALYSIS OF A DETERMINISTIC STOCHASTIC ORBIT
Kaufman, Allan N.; Abarbanel, Henry D.I.; Grebogi, Celso
1980-05-01
If the solution of a deterministic equation is stochastic (in the sense of orbital instability), it can be subjected to a statistical analysis. This is illustrated for a coded orbit of the Chirikov mapping. Statistical dependence and the Markov assumption are tested. The Kolmogorov-Sinai entropy is related to the probability distribution for the orbit.
Statistical analysis of histopathological endpoints.
Green, John W; Springer, Timothy A; Saulnier, Amy N; Swintek, Joe
2014-05-01
Histopathological assessments of fish from aquatic ecotoxicology studies are being performed with increasing frequency. Aquatic ecotoxicology studies performed for submission to regulatory agencies are usually conducted with multiple subjects (e.g., fish) in each of multiple vessels (replicates) within a water control and within each of several concentrations of a test substance. A number of histopathological endpoints are evaluated in each fish, and a severity score is generally recorded for each endpoint. The severity scores are often recorded using a nonquantitative scale of 0 to 4, with 0 indicating no effect, 1 indicating minimal effect, through 4 for severe effect. Statistical methods often used to analyze these scores suffer from several shortcomings: computing average scores as though scores were quantitative values, considering only the frequency of abnormality while ignoring severity, ignoring any concentration-response trend, and ignoring the possible correlation between responses of individuals within test vessels. A new test, the Rao-Scott Cochran-Armitage by Slices (RSCABS), is proposed that incorporates the replicate vessel experimental design and the biological expectation that the severity of the effect tends to increase with increasing doses or concentrations, while retaining the individual subject scores and taking into account the severity as well as frequency of scores. A power simulation and examples demonstrate the performance of the test. R-based software has been developed to carry out this test and is available free of charge at www.epa.gov/med/Prods_Pubs/rscabs.htm. The SAS-based RSCABS software is available from the first and third authors. PMID:24464649
Advice on statistical analysis for Circulation Research.
Kusuoka, Hideo; Hoffman, Julien I E
2002-10-18
Since the late 1970s when many journals published articles warning about the misuse of statistical methods in the analysis of data, researchers have become more careful about statistical analysis, but errors including low statistical power and inadequate analysis of repeated-measurement studies are still prevalent. In this review, several statistical methods are introduced that are not always familiar to basic and clinical cardiologists but may be useful for revealing the correct answer from the data. The aim of this review is not only to draw the attention of investigators to these tests but also to stress the conditions in which they are applicable. These methods are now generally available in statistical program packages. Researchers need not know how to calculate the statistics from the data but are required to select the correct method from the menu and interpret the statistical results accurately. With the choice of appropriate statistical programs, the issue is no longer how to do the test but when to do it. PMID:12386142
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.
Survival analysis of aging aircraft
NASA Astrophysics Data System (ADS)
Benavides, Samuel
This study pushes systems engineering of aging aircraft beyond the boundaries of empirical and deterministic modeling by making a sharp break with the traditional laboratory-derived corrosion prediction algorithms that have shrouded real-world failures of aircraft structure. At the heart of this problem is the aeronautical industry's inability to be forthcoming in an accurate model that predicts corrosion failures in aircraft in spite of advances in corrosion algorithms or improvements in simulation and modeling. The struggle to develop accurate corrosion probabilistic models stems from a multitude of real-world interacting variables that synergistically influence corrosion in convoluted and complex ways. This dissertation, in essence, offers a statistical framework for the analysis of structural airframe corrosion failure by utilizing real-world data while considering the effects of interacting corrosion variables. This study injects realism into corrosion failures of aging aircraft systems by accomplishing four major goals related to the conceptual and methodological framework of corrosion modeling. First, this work connects corrosion modeling from the traditional, laboratory derived algorithms to corrosion failures in actual operating aircraft. This work augments physics-based modeling by examining the many confounding and interacting variables, such as environmental, geographical and operational, that impact failure of airframe structure. Examined through the lens of censored failure data from aircraft flying in a maritime environment, this study enhances the understanding between the triad of the theoretical, laboratory and real-world corrosion. Secondly, this study explores the importation and successful application of an advanced biomedical statistical tool---survival analysis---to model censored corrosion failure data. This well-grounded statistical methodology is inverted from a methodology that analyzes survival to one that examines failures. Third, this
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.
Statistical energy analysis computer program, user's guide
NASA Technical Reports Server (NTRS)
Trudell, R. W.; Yano, L. I.
1981-01-01
A high frequency random vibration analysis, (statistical energy analysis (SEA) method) is examined. The SEA method accomplishes high frequency prediction of arbitrary structural configurations. A general SEA computer program is described. A summary of SEA theory, example problems of SEA program application, and complete program listing are presented.
Multiset Statistics for Gene Set Analysis
Newton, Michael A.; Wang, Zhishi
2015-01-01
An important data analysis task in statistical genomics involves the integration of genome-wide gene-level measurements with preexisting data on the same genes. A wide variety of statistical methodologies and computational tools have been developed for this general task. We emphasize one particular distinction among methodologies, namely whether they process gene sets one at a time (uniset) or simultaneously via some multiset technique. Owing to the complexity of collections of gene sets, the multiset approach offers some advantages, as it naturally accommodates set-size variations and among-set overlaps. However, this approach presents both computational and inferential challenges. After reviewing some statistical issues that arise in uniset analysis, we examine two model-based multiset methods for gene list data. PMID:25914887
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...
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…
Bayesian Statistics for Biological Data: Pedigree Analysis
ERIC Educational Resources Information Center
Stanfield, William D.; Carlton, Matthew A.
2004-01-01
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
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
Unified statistical approach to cortical thickness analysis.
Chung, Moo K; Robbins, Steve; Evans, Alan C
2005-01-01
This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of data smoothing and analysis framework. The human brain cortex is a highly convoluted surface. Due to the convoluted non-Euclidean surface geometry, data smoothing and analysis on the cortex are inherently difficult. When measurements lie on a curved surface, it is natural to assign kernel smoothing weights based on the geodesic distance along the surface rather than the Euclidean distance. We present a new data smoothing framework that address this problem implicitly without actually computing the geodesic distance and present its statistical properties. Afterwards, the statistical inference is based on the random field theory based multiple comparison correction. As an illustration, we have applied the method in detecting the regions of abnormal cortical thickness in 16 high functioning autistic children. PMID:17354731
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
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
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
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.
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.
A statistical analysis of NMR spectrometer noise.
Grage, Halfdan; Akke, Mikael
2003-05-01
Estimation of NMR spectral parameters, using e.g. maximum likelihood methods, is commonly based on the assumption of white complex Gaussian noise in the signal obtained by quadrature detection. Here we present a statistical analysis with the purpose of discussing and testing the validity of this fundamental assumption. Theoretical expressions are derived for the correlation structure of the noise under various conditions, showing that in general the noise in the sampled signal is not strictly white, even if the thermal noise in the receiver steps prior to digitisation can be characterised as white Gaussian noise. It is shown that the noise correlation properties depend on the ratio between the sampling frequency and the filter cut-off frequency, as well as the filter characteristics. The theoretical analysis identifies conditions that are expected to yield non-white noise in the sampled signal. Extensive statistical characterisation of experimental noise confirms the theoretical predictions. The statistical methods outlined here are also useful for residual analysis in connection with validation of the model and the parameter estimates. PMID:12762994
Statistical Analysis of Spectra with Many Lines
NASA Astrophysics Data System (ADS)
van Dyk, D. A.; Kang, H. S.; Connors, A.; Kashyap, V. L.; Siemiginowska, A.
2001-12-01
Please join us in our wider effort to engage the strengths of modern computational statistics methods in solving challenging stellar and solar data analysis problems. As just one example (of a great breadth of possibilities) consider analyzing a spectrum with a very large number of lines. Some of these may be faint, merged, indistinguishable from each other and the underlying smooth continuum. The ensemble of line intensities follows a predictable distribution. The shape of this distribution depends on the properties of the source, e.g., its temperature, abundances, and emission measure. Hence, a better understanding of the distribution of line fluxes in a particular source may tighten our inference for other model parameters such as temperature---even when very few lines are actually easy to distinguish. To take advantage of this structure, we directly model the distribution of the line fluxes rather than fitting each line flux directly or ``investing'' the emissivities to get a DEM. Statistically, this strategy reduces the number of free parameters, which we expect will lead to improved statistical properties. We believe this method holds much promise for improved analysis, especially for low count sources. For example, we expect this method to correctly account for the ``pseudo-continuum'' that results from the large number of faint, unresolvable lines in X-ray grating spectra. Moreover, our statistical methods should apply directly to other settings involving a multitude of lines such as timing data. We hope that these methods will increase our statistical power to set the continuum level in the presence of a multitude of lines and to distinguish weak lines from fluctuations in the continuum. Funding for this project partially provided by NSF grant and DMS-01-04129 and by NASA Contract NAS8-39073 (CXC).
Statistical Tolerance and Clearance Analysis for Assembly
NASA Technical Reports Server (NTRS)
Lee, S.; Yi, C.
1996-01-01
Tolerance is inevitable because manufacturing exactly equal parts is known to be impossible. Furthermore, the specification of tolerances is an integral part of product design since tolerances directly affect the assemblability, functionality, manufacturability, and cost effectiveness of a product. In this paper, we present statistical tolerance and clearance analysis for the assembly. Our proposed work is expected to make the following contributions: (i) to help the designers to evaluate products for assemblability, (ii) to provide a new perspective to tolerance problems, and (iii) to provide a tolerance analysis tool which can be incorporated into a CAD or solid modeling system.
Meaningful statistical analysis of large computational clusters.
Gentile, Ann C.; Marzouk, Youssef M.; Brandt, James M.; Pebay, Philippe Pierre
2005-07-01
Effective monitoring of large computational clusters demands the analysis of a vast amount of raw data from a large number of machines. The fundamental interactions of the system are not, however, well-defined, making it difficult to draw meaningful conclusions from this data, even if one were able to efficiently handle and process it. In this paper we show that computational clusters, because they are comprised of a large number of identical machines, behave in a statistically meaningful fashion. We therefore can employ normal statistical methods to derive information about individual systems and their environment and to detect problems sooner than with traditional mechanisms. We discuss design details necessary to use these methods on a large system in a timely and low-impact fashion.
Apparatus for statistical time-series analysis of electrical signals
NASA Technical Reports Server (NTRS)
Stewart, C. H. (Inventor)
1973-01-01
An apparatus for performing statistical time-series analysis of complex electrical signal waveforms, permitting prompt and accurate determination of statistical characteristics of the signal is presented.
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. PMID:23117406
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.
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.
Statistical Analysis to Select Evacuation Route
NASA Astrophysics Data System (ADS)
Musyarof, Z.; Sutarto, D. Y.; Atika, D. R.; Fajriya Hakim, R. B.
2015-06-01
Each country should be responsible for the safety of people, especially responsible for the safety of people living in disaster-prone areas. One of those services is provides evacuation route for them. But all this time, the selection of evacuation route is seem does not well organized, it could be seen that when a disaster happen, there will be many accumulation of people on the steps of evacuation route. That condition is dangerous to people because hampers evacuation process. By some methods in Statistical analysis, author tries to give a suggestion how to prepare evacuation route which is organized and based on people habit. Those methods are association rules, sequential pattern mining, hierarchical cluster analysis and fuzzy logic.
Statistical utopianism in the age of aristocratic efficiency.
Porter, Theodore
2002-01-01
The modern history of science is commonly associated with an inexorable move toward increasing specialization and, perhaps, a proliferation of expert discourses at the expense of public discourse. This paper concerns the standing of science as a basis for public authority in late-Victorian and Edwardian Britain, and suggests that, in relation to the political order, this standing remained tenuous. These themes are exemplified by the career of Karl Pearson, founder of the modern school of mathematical statistics and something of a social visionary. Like Huxley and other scientific naturalists, Pearson wished to incorporate science into a reinvigorated "general culture" and in this way to reshape an elite. Statistics, seemingly the archetypal form of specialist expertise, was conceived as an almost utopian program to advance intelligence and mortality in what he sometimes referred to as a new aristocracy. PMID:12385323
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
Environmental studies: Mathematical, computational, and statistical analysis
Wheeler, M.F.
1996-12-31
The Summer Program on Mathematical, Computational, and Statistical Analyses in Environmental Studies held 6--31 July 1992 was designed to provide a much needed interdisciplinary forum for joint exploration of recent advances in the formulation and application of (A) environmental models, (B) environmental data and data assimilation, (C) stochastic modeling and optimization, and (D) global climate modeling. These four conceptual frameworks provided common themes among a broad spectrum of specific technical topics at this workshop. The program brought forth a mix of physical concepts and processes such as chemical kinetics, atmospheric dynamics, cloud physics and dynamics, flow in porous media, remote sensing, climate statistical, stochastic processes, parameter identification, model performance evaluation, aerosol physics and chemistry, and data sampling together with mathematical concepts in stiff differential systems, advective-diffusive-reactive PDEs, inverse scattering theory, time series analysis, particle dynamics, stochastic equations, optimal control, and others. Nineteen papers are presented in this volume. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.
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).
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 ultrasonic measurements in concrete
NASA Astrophysics Data System (ADS)
Chiang, Chih-Hung; Chen, Po-Chih
2002-05-01
Stress wave techniques such as measurements of ultrasonic pulse velocity are often used to evaluate concrete quality in structures. For proper interpretation of measurement results, the dependence of pulse transit time on the average acoustic impedance and the material homogeneity along the sound path need to be examined. Semi-direct measurement of pulse velocity could be more convenient than through transmission measurement. It is not necessary to assess both sides of concrete floors or walls. A novel measurement scheme is proposed and verified based on statistical analysis. It is shown that Semi-direct measurements are very effective for gathering large amount of pulse velocity data from concrete reference specimens. The variability of measurements is comparable with that reported by American Concrete Institute using either break-off or pullout tests.
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…
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
Statistical Analysis of Streamflow Trends in Slovenia
NASA Astrophysics Data System (ADS)
Jurko, M.; Kobold, M.; Mikoš, M.
2009-04-01
According to climate change, trends of river discharges were analyzed showing the hydrological change and future projections of hydrological behaviour in Slovenia. In last years droughts and floods are becoming more and more frequent. In the statistical analysis of streamflow trends of Slovenian rivers, available data on the low, mean and high discharges were examined using mean daily discharges and the Hydrospect software, which was developed under the auspices of WMO for detecting changes in hydrological data (Kundzewicz and Robson, 2000). The Mann-Kendall test was applied for the estimation of trends in the river flow index series. Trend analysis requires long records of observation to distinguish climate change-induced trends from climate variability. The problems of missing values, seasonal and other short-term fluctuations or anthropogenic impacts and lack of homogeneity of data due to the changes in instruments and observation techniques are frequently present in existing hydrological data sets. Therefore the analysis was carried out for 77 water gauging stations representatively distributed across Slovenia with sufficiently long and reliable continuous data sets. The average length of the data sets from the selected water gauging stations is about 50 years. Different indices were used to assess the temporal variation of discharges: annual mean daily discharge, annual maximum daily discharge, two magnitude and frequency series by peak-over-threshold (POT) approach (POT1 and POT3), and two low flow indices describing the different duration of low flows (7 and 30 days). The clustering method was used to classify the results of trends into groups. The assumption of a general decrease of water quantities in Slovenian rivers was confirmed. The annual mean daily discharges of the analyzed water gauging stations show a significant negative trend for the majority of the stations. Similar results with lower statistical significance show annual minimum 7-day and 30
Statistical image analysis of longitudinal RAVENS images
Lee, Seonjoo; Zipunnikov, Vadim; Reich, Daniel S.; Pham, Dzung L.
2015-01-01
Regional analysis of volumes examined in normalized space (RAVENS) are transformation images used in the study of brain morphometry. In this paper, RAVENS images are analyzed using a longitudinal variant of voxel-based morphometry (VBM) and longitudinal functional principal component analysis (LFPCA) for high-dimensional images. We demonstrate that the latter overcomes the limitations of standard longitudinal VBM analyses, which does not separate registration errors from other longitudinal changes and baseline patterns. This is especially important in contexts where longitudinal changes are only a small fraction of the overall observed variability, which is typical in normal aging and many chronic diseases. Our simulation study shows that LFPCA effectively separates registration error from baseline and longitudinal signals of interest by decomposing RAVENS images measured at multiple visits into three components: a subject-specific imaging random intercept that quantifies the cross-sectional variability, a subject-specific imaging slope that quantifies the irreversible changes over multiple visits, and a subject-visit specific imaging deviation. We describe strategies to identify baseline/longitudinal variation and registration errors combined with covariates of interest. Our analysis suggests that specific regional brain atrophy and ventricular enlargement are associated with multiple sclerosis (MS) disease progression. PMID:26539071
Time Series Analysis Based on Running Mann Whitney Z Statistics
Technology Transfer Automated Retrieval System (TEKTRAN)
A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...
Axelrad, Daniel A; Cohen, Jonathan
2011-01-01
The effects of chemical exposures during pregnancy on children's health have been an increasing focus of environmental health research in recent years, leading to greater interest in biomonitoring of chemicals in women of childbearing age in the general population. Measurements of mercury in blood from the National Health and Nutrition Examination Survey are frequently reported for "women of childbearing age," defined to be of ages 16-49 years. The intent is to represent prenatal chemical exposure, but blood mercury levels increase with age. Furthermore, women of different ages have different probabilities of giving birth. We evaluated options to address potential bias in biomonitoring summary statistics for women of childbearing age by accounting for age-specific probabilities of giving birth. We calculated median and 95th percentile levels of mercury, PCBs, and cotinine using these approaches: option 1: women aged 16-49 years without natality adjustment; option 2: women aged 16-39 years without natality adjustment; option 3: women aged 16-49 years, adjusted for natality by age; option 4: women aged 16-49 years, adjusted for natality by age and race/ethnicity. Among the three chemicals examined, the choice of option has the greatest impact on estimated levels of serum PCBs, which are strongly associated with age. Serum cotinine levels among Black non-Hispanic women of childbearing age are understated when age-specific natality is not considered. For characterizing in utero exposures, adjustment using age-specific natality provides a substantial improvement in estimation of biomonitoring summary statistics. PMID:21035114
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
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
Refining Martian Ages and Understanding Geological Processes From Cratering Statistics
NASA Technical Reports Server (NTRS)
Hartmann, William K.
2005-01-01
Senior Scientist William K. Hartman presents his final report on Mars Data Analysis Program grant number NAG5-12217: The third year of the three-year program was recently completed in mid-2005. The program has been extremely productive in research and data analysis regarding Mars, especially using Mars Global Surveyor and Mars Odyssey imagery. In the 2005 alone, three papers have already been published, to which this work contributed.1) Hartmann, W. K. 200.5. Martian cratering 8. Isochron refinement and the history of Martian geologic activity Icarus 174, 294-320. This paper is a summary of my entire program of establishing Martian chronology through counts of Martian impact craters. 2) Arfstrom, John, and W. K. Hartmann 2005. Martian flow features, moraine-like rieges, and gullies: Terrestrial analogs and interrelationships. Icarus 174,32 1-335. This paper makes pioneering connections between Martian glacier-like features and terrestrial glacial features. 3) Hartmann, W.K., D. Winterhalter, and J. Geiss. 2005 Chronology and Physical Evolution of Planet Mars. In The Solar System and Beyond: Ten Years of ISSI (Bern: International Space Science Institute). This is a summary of work conducted at the International Space Science Institute with an international team, emphasizing our publication of a conference volume about Mars, edited by Hartmann and published in 2001.
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…
Statistical Error Analysis for Digital Recursive Filters
NASA Astrophysics Data System (ADS)
Wu, Kevin Chi-Rung
The study of arithmetic roundoff error has attracted many researchers to investigate how the signal-to-noise ratio (SNR) is affected by algorithmic parameters, especially since the VLSI (Very Large Scale Integrated circuits) technologies have become more promising for digital signal processing. Typically, digital signal processing involving, either with or without matrix inversion, will have tradeoffs on speed and processor cost. Hence, the problems of an area-time efficient matrix computation and roundoff error behavior analysis will play an important role in this dissertation. A newly developed non-Cholesky square-root matrix will be discussed which precludes the arithmetic roundoff error over some interesting operations, such as complex -valued matrix inversion with its SNR analysis and error propagation effects. A non-CORDIC parallelism approach for complex-valued matrix will be presented to upgrade speed at the cost of moderate increase of processor. The lattice filter will also be looked into, in such a way, that one can understand the SNR behavior under the conditions of different inputs in the joint process system. Pipelining technique will be demonstrated to manifest the possibility of high-speed non-matrix-inversion lattice filter. Floating point arithmetic modelings used in this study have been focused on effective methodologies that have been proved to be reliable and feasible. With the models in hand, we study the roundoff error behavior based on some statistical assumptions. Results are demonstrated by carrying out simulation to show the feasibility of SNR analysis. We will observe that non-Cholesky square-root matrix has advantage of saving a time of O(n^3) as well as a reduced realization cost. It will be apparent that for a Kalman filter the register size is increasing significantly, if pole of the system matrix is moving closer to the edge of the unit circle. By comparing roundoff error effect due to floating-point and fixed-point arithmetics, we
Practical Issues in Component Aging Analysis
Dana L. Kelly; Andrei Rodionov; Jens Uwe-Klugel
2008-09-01
This paper examines practical issues in the statistical analysis of component aging data. These issues center on the stochastic process chosen to model component failures. The two stochastic processes examined are repair same as new, leading to a renewal process, and repair same as old, leading to a nonhomogeneous Poisson process. Under the first assumption, times between failures can treated as statistically independent observations from a stationary process. The common distribution of the times between failures is called the renewal distribution. Under the second process, the times between failures will not be independently and identically distributed, and one cannot simply fit a renewal distribution to the cumulative failure times or the times between failures. The paper illustrates how the assumption made regarding the repair process is crucial to the analysis. Besides the choice of stochastic process, other issues that are discussed include qualitative graphical analysis and simple nonparametric hypothesis tests to help judge which process appears more appropriate. Numerical examples are presented to illustrate the issues discussed in the paper.
Statistical Analysis of Examination to Detect Cheating.
ERIC Educational Resources Information Center
Code, Ronald P.
1985-01-01
A number of statistical procedures that were developed in 1983 at the University of Medicine and Dentistry of New Jersey-Rutgers Medical School to verify the suspicion that a student cheated during an examination are described. (MLW)
Detection and analysis of statistical differences in anatomical shape.
Golland, Polina; Grimson, W Eric L; Shenton, Martha E; Kikinis, Ron
2005-02-01
We present a computational framework for image-based analysis and interpretation of statistical differences in anatomical shape between populations. Applications of such analysis include understanding developmental and anatomical aspects of disorders when comparing patients versus normal controls, studying morphological changes caused by aging, or even differences in normal anatomy, for example, differences between genders. Once a quantitative description of organ shape is extracted from input images, the problem of identifying differences between the two groups can be reduced to one of the classical questions in machine learning of constructing a classifier function for assigning new examples to one of the two groups while making as few misclassifications as possible. The resulting classifier must be interpreted in terms of shape differences between the two groups back in the image domain. We demonstrate a novel approach to such interpretation that allows us to argue about the identified shape differences in anatomically meaningful terms of organ deformation. Given a classifier function in the feature space, we derive a deformation that corresponds to the differences between the two classes while ignoring shape variability within each class. Based on this approach, we present a system for statistical shape analysis using distance transforms for shape representation and the support vector machines learning algorithm for the optimal classifier estimation and demonstrate it on artificially generated data sets, as well as real medical studies. PMID:15581813
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.
Statistical measures for workload capacity analysis.
Houpt, Joseph W; Townsend, James T
2012-10-01
A critical component of how we understand a mental process is given by measuring the effect of varying the workload. The capacity coefficient (Townsend & Nozawa, 1995; Townsend & Wenger, 2004) is a measure on response times for quantifying changes in performance due to workload. Despite its precise mathematical foundation, until now rigorous statistical tests have been lacking. In this paper, we demonstrate statistical properties of the components of the capacity measure and propose a significance test for comparing the capacity coefficient to a baseline measure or two capacity coefficients to each other. PMID:23175582
EXPERIMENTAL DESIGN: STATISTICAL CONSIDERATIONS AND ANALYSIS
Technology Transfer Automated Retrieval System (TEKTRAN)
In this book chapter, information on how field experiments in invertebrate pathology are designed and the data collected, analyzed, and interpreted is presented. The practical and statistical issues that need to be considered and the rationale and assumptions behind different designs or procedures ...
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.
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
2014-10-01
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. PMID:25213136
A statistical package for computing time and frequency domain analysis
NASA Technical Reports Server (NTRS)
Brownlow, J.
1978-01-01
The spectrum analysis (SPA) program is a general purpose digital computer program designed to aid in data analysis. The program does time and frequency domain statistical analyses as well as some preanalysis data preparation. The capabilities of the SPA program include linear trend removal and/or digital filtering of data, plotting and/or listing of both filtered and unfiltered data, time domain statistical characterization of data, and frequency domain statistical characterization of data.
Computer program performs statistical analysis for random processes
NASA Technical Reports Server (NTRS)
Newberry, M. H.
1966-01-01
Random Vibration Analysis Program /RAVAN/ performs statistical analysis on a number of phenomena associated with flight and captive tests, but can also be used in analyzing data from many other random processes.
Personal Ad Content Analysis Teaches Statistical Applications.
ERIC Educational Resources Information Center
Rajecki, D. W.
2002-01-01
Focuses on an undergraduate student project which asked students to write a paper based on their examination of age preferences indicated by writers of personal advertisements appearing in newspapers. Reports on the student responses to this project using a questionnaire. Examines the student scores on the final examination for the course. (CMK)
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 Random Number Generators
NASA Astrophysics Data System (ADS)
Accardi, Luigi; Gäbler, Markus
2011-01-01
In many applications, for example cryptography and Monte Carlo simulation, there is need for random numbers. Any procedure, algorithm or device which is intended to produce such is called a random number generator (RNG). What makes a good RNG? This paper gives an overview on empirical testing of the statistical properties of the sequences produced by RNGs and special software packages designed for that purpose. We also present the results of applying a particular test suite--TestU01-- to a family of RNGs currently being developed at the Centro Interdipartimentale Vito Volterra (CIVV), Roma, Italy.
Uncertainty analysis of statistical downscaling methods
NASA Astrophysics Data System (ADS)
Khan, Mohammad Sajjad; Coulibaly, Paulin; Dibike, Yonas
2006-03-01
Three downscaling models namely Statistical Down-Scaling Model (SDSM), Long Ashton Research Station Weather Generator (LARS-WG) model and Artificial Neural Network (ANN) model have been compared in terms various uncertainty assessments exhibited in their downscaled results of daily precipitation, daily maximum and minimum temperatures. In case of daily maximum and minimum temperature, uncertainty is assessed by comparing monthly mean and variance of downscaled and observed daily maximum and minimum temperature at each month of the year at 95% confidence level. In addition, uncertainties of the monthly means and variances of downscaled daily temperature have been calculated using 95% confidence intervals, which are compared with the observed uncertainties of means and variances. In daily precipitation downscaling, in addition to comparing means and variances, uncertainties have been assessed by comparing monthly mean dry and wet spell lengths and their confidence intervals, cumulative frequency distributions (cdfs) of monthly mean of daily precipitation, and the distributions of monthly wet and dry days for observed and downscaled daily precipitation. The study has been carried out using 40 years of observed and downscaled daily precipitation, daily maximum and minimum temperature data using NCEP (National Center for Environmental Prediction) reanalysis predictors starting from 1961 to 2000. The uncertainty assessment results indicate that the SDSM is the most capable of reproducing various statistical characteristics of observed data in its downscaled results with 95% confidence level, the ANN is the least capable in this respect, and the LARS-WG is in between SDSM and ANN.
On the statistical analysis of maximal magnitude
NASA Astrophysics Data System (ADS)
Holschneider, M.; Zöller, G.; Hainzl, S.
2012-04-01
We show how the maximum expected magnitude within a time horizon [0,T] may be estimated from earthquake catalog data within the context of truncated Gutenberg-Richter statistics. We present the results in a frequentist and in a Bayesian setting. Instead of deriving point estimations of this parameter and reporting its performance in terms of expectation value and variance, we focus on the calculation of confidence intervals based on an imposed level of confidence α. We present an estimate of the maximum magnitude within an observational time interval T in the future, given a complete earthquake catalog for a time period Tc in the past and optionally some paleoseismic events. We argue that from a statistical point of view the maximum magnitude in a time window is a reasonable parameter for probabilistic seismic hazard assessment, while the commonly used maximum possible magnitude for all times does almost certainly not allow the calculation of useful (i.e. non-trivial) confidence intervals. In the context of an unbounded GR law we show, that Jeffreys invariant prior distribtution yields normalizable posteriors. The predictive distribution based on this prior is explicitely computed.
Statistical Seismic Landslide Analysis: an Update
NASA Astrophysics Data System (ADS)
Lee, Chyi-Tyi
2015-04-01
Landslides are secondary or induced features, whose recurrence is controlled by the repetition of triggering events, such as earthquakes or heavy rainfall. This makes seismic landslide hazard analysis more complicated than ordinary seismic hazard analysis, and it requires multi-stage analysis. First, susceptibility analysis is utilized to divide a region into successive classes. Then, it is necessary to construct a relationship between the probability of landslide failure and earthquake intensity for each susceptibility class for a region, or to find the probability of failure surface using the susceptibility value and earthquake intensity as independent variables at the study region. Then, hazard analysis for the exceedance probability of earthquake intensity is performed. Finally, an analysis of the spatial probability of landslide failure under a certain return-period earthquake is drawn. This study uses data for Chi-Chi earthquake induced landslides as the training data set to perform the susceptibility analysis and probability of failure surface analysis. A regular probabilistic seismic hazard analysis is also conducted to map different return-period Arias intensities. Finally a seismic landslide hazard map for the whole of Taiwan is provided.
Diagnostic rhyme test statistical analysis programs
NASA Astrophysics Data System (ADS)
Sim, A.; Bain, R.; Belyavin, A. J.; Pratt, R. L.
1991-08-01
The statistical techniques and associated computer programs used to analyze data from Diagnostic Rhyme Test (DRT) are described. The DRT is used extensively for assessing the intelligibility of military communications systems and became an accepted NATO standard for testing linear predictive coders. The DRT vocabulary comprises ninety six minimally contrasting rhyming word pairs, the initial consonants of which differ only by a single acoustic feature, or attribute. There are six such attributes: voicing, nasality, sustention, silibation, graveness, and compactness. The attribute voicing is present when the vocal cords are excited: in the word pair 'veal-feel', the consonant 'v' is voiced, but the constant 'f' is unvoiced. The procedure for the implementation of the DRT is presented. To ensure the stability of the results, tests using not less than eight talkers and eight listeners are conducted.
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.
Statistical Analysis of Galaxy Redshift Surveys
NASA Astrophysics Data System (ADS)
Percival, Will J.
2008-12-01
The statistical distribution of galaxies encodes significant cosmological information. For Gaussian random fields, 2-point functions, the correlation function in real space and the power spectrum in Fourier space are complete, and offer the most direct route to this information. In this proceedings, I consider three mechanisms for extracting information from the power spectrum. The relative amplitude of small-scale and large-scale power can constrain the matter-radiation equality scale, but this is hard to disentangle from galaxy bias. Baryon Acoustic Oscillations are more robust to galaxy bias effects, and lead to constraints the evolution of the Universe by providing a standard ruler whose distance can be compared at different redshifts. Redshift-Space distortions, resulting from galaxy peculiar velocities can be used to measure the cosmological growth of structure, and are immune to density bias as the velocities are independent of galaxy properties.
Wu, Minjie; Kumar, Anand; Yang, Shaolin
2016-05-01
Superficial white matter (SWM) lies immediately beneath cortical gray matter and consists primarily of short association fibers. The characteristics of SWM and its development and aging were seldom examined in the literature and warrant further investigation. Magnetization transfer imaging is sensitive to myelin changes in the white matter. Using an innovative multimodal imaging analysis approach, vertex-based surface statistics (VBSS), the current study vertexwise mapped age-related changes of magnetization transfer ratio (MTR) in SWM from young adulthood to old age (30-85 years, N = 66). Results demonstrated regionally selective and temporally heterochronologic changes of SWM MTR with age, including (1) inverted U-shaped trajectories of SWM MTR in the rostral middle frontal, medial temporal, and temporoparietal regions, suggesting continuing myelination and protracted maturation till age 40-50 years and accelerating demyelination at age 60 and beyond, (2) linear decline of SWM MTR in the middle and superior temporal, and pericalcarine areas, indicating early maturation and less acceleration in age-related degeneration, and (3) no significant changes of SWM MTR in the primary motor, somatosensory and auditory regions, suggesting resistance to age-related deterioration. We did not observe similar patterns of changes in cortical thickness in our sample, suggesting the observed SWM MTR changes are not due to cortical atrophy. Hum Brain Mapp 37:1759-1769, 2016. © 2016 Wiley Periodicals, Inc. PMID:26955787
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.
Statistical Evaluation of Time Series Analysis Techniques
NASA Technical Reports Server (NTRS)
Benignus, V. A.
1973-01-01
The performance of a modified version of NASA's multivariate spectrum analysis program is discussed. A multiple regression model was used to make the revisions. Performance improvements were documented and compared to the standard fast Fourier transform by Monte Carlo techniques.
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.
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
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
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.
Statistical analysis of fixed income market
NASA Astrophysics Data System (ADS)
Bernaschi, Massimo; Grilli, Luca; Vergni, Davide
2002-05-01
We present cross and time series analysis of price fluctuations in the US Treasury fixed income market. Bonds have been classified according to a suitable metric based on the correlation among them. The classification shows how the correlation among fixed income securities depends strongly on their maturity. We study also the structure of price fluctuations for single time series.
A statistical model including age to predict passenger postures in the rear seats of automobiles.
Park, Jangwoon; Ebert, Sheila M; Reed, Matthew P; Hallman, Jason J
2016-06-01
Few statistical models of rear seat passenger posture have been published, and none has taken into account the effects of occupant age. This study developed new statistical models for predicting passenger postures in the rear seats of automobiles. Postures of 89 adults with a wide range of age and body size were measured in a laboratory mock-up in seven seat configurations. Posture-prediction models for female and male passengers were separately developed by stepwise regression using age, body dimensions, seat configurations and two-way interactions as potential predictors. Passenger posture was significantly associated with age and the effects of other two-way interaction variables depended on age. A set of posture-prediction models are presented for women and men, and the prediction results are compared with previously published models. This study is the first study of passenger posture to include a large cohort of older passengers and the first to report a significant effect of age for adults. The presented models can be used to position computational and physical human models for vehicle design and assessment. Practitioner Summary: The significant effects of age, body dimensions and seat configuration on rear seat passenger posture were identified. The models can be used to accurately position computational human models or crash test dummies for older passengers in known rear seat configurations. PMID:26328769
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…
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…
Explorations in Statistics: The Analysis of Ratios and Normalized Data
ERIC Educational Resources Information Center
Curran-Everett, Douglas
2013-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of "Explorations in Statistics" explores the analysis of ratios and normalized--or standardized--data. As researchers, we compute a ratio--a numerator divided by a denominator--to compute a…
NASA Technical Reports Server (NTRS)
Neukum, G.
1988-01-01
In the absence of dates derived from rock samples, impact crater frequencies are commonly used to date Martian surface units. All models for absolute dating rely on the lunar cratering chronology and on the validity of its extrapolation to Martian conditions. Starting from somewhat different lunar chronologies, rather different Martian cratering chronologies are found in the literature. Currently favored models are compared. The differences at old ages are significant, the differences at younger ages are considerable and give absolute ages for the same crater frequencies as different as a factor of 3. The total uncertainty could be much higher, though, since the ratio of lunar to Martian cratering rate which is of basic importance in the models is believed to be known no better than within a factor of 2. Thus, it is of crucial importance for understanding the the evolution of Mars and determining the sequence of events to establish an unambiguous Martian cratering chronology from crater statistics in combination with clean radiometric ages of returned Martian samples. For the dating goal, rocks should be as pristine as possible from a geologically simple area with a one-stage emplacement history of the local formation. A minimum of at least one highland site for old ages, two intermediate-aged sites, and one very young site is needed.
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.
Improving the Statistical Methodology of Astronomical Data Analysis
NASA Astrophysics Data System (ADS)
Feigelson, Eric D.; Babu, Gutti Jogesh
Contemporary observational astronomers are generally unfamiliar with the extensive advances made in mathematical and applied statistics during the past several decades. Astronomical problems can often be addressed by methods developed in statistical fields such as spatial point processes, density estimation, Bayesian statistics, and sampling theory. The common problem of bivariate linear regression illustrates the need for sophisticated methods. Astronomical problems often require combinations of ordinary least-squares lines, double-weighted and errors-in-variables models, censored and truncated regressions, each with its own error analysis procedure. The recent conference Statistical Challenges in Modern Astronomy highlighted issues of mutual interest to statisticians and astronomers including clustering of point processes and time series analysis. We conclude with advice on how the astronomical community can advance its statistical methodology with improvements in education of astrophysicists, collaboration and consultation with professional statisticians, and acquisition of new software.
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.
The HONEYPOT Randomized Controlled Trial Statistical Analysis Plan
Pascoe, Elaine Mary; Lo, Serigne; Scaria, Anish; Badve, Sunil V.; Beller, Elaine Mary; Cass, Alan; Hawley, Carmel Mary; Johnson, David W.
2013-01-01
♦ Background: The HONEYPOT study is a multicenter, open-label, blinded-outcome, randomized controlled trial designed to determine whether, compared with standard topical application of mupirocin for nasal staphylococcal carriage, exit-site application of antibacterial honey reduces the rate of catheter-associated infections in peritoneal dialysis patients. ♦ Objective: To make public the pre-specified statistical analysis principles to be adhered to and the procedures to be performed by statisticians who will analyze the data for the HONEYPOT trial. ♦ Methods: Statisticians and clinical investigators who were blinded to treatment allocation and treatment-related study results and who will remain blinded until the central database is locked for final data extraction and analysis determined the statistical methods and procedures to be used for analysis and wrote the statistical analysis plan. The plan describes basic analysis principles, methods for dealing with a range of commonly encountered data analysis issues, and the specific statistical procedures for analyzing the primary, secondary, and safety outcomes. ♦ Results: A statistical analysis plan containing the pre-specified principles, methods, and procedures to be adhered to in the analysis of the data from the HONEYPOT trial was developed in accordance with international guidelines. The structure and content of the plan provide sufficient detail to meet the guidelines on statistical principles for clinical trials produced by the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use. ♦ Conclusions: Making public the pre-specified statistical analysis plan for the HONEYPOT trial minimizes the potential for bias in the analysis of trial data and the interpretation and reporting of trial results. PMID:23843589
A Warning System for Stromboli Volcano Based on Statistical Analysis
NASA Astrophysics Data System (ADS)
Nunnari, Giuseppe; Puglisi, Giuseppe; Spata, Alessandro
2008-08-01
In this paper we describe a warning system based on statistical analysis for the purpose of monitoring ground deformation at the Sciara del Fuoco (Stromboli Volcano, Sicily). After a statistical analysis of ground deformation time-series measured at Stromboli by the monitoring system known as THEODOROS (THEOdolite and Distancemeter Robot Observatory of Stromboli), the paper describes the solution adopted for implementing the warning system. A robust statistical index has been defined in order to evaluate the movements of the area. A fuzzy approach has been proposed to evaluate an AI (Alarm Intensity) index which indicates the level of hazard of the Sciara del Fuoco sliding.
Cohen, Alan A; Milot, Emmanuel; Li, Qing; Legault, Véronique; Fried, Linda P; Ferrucci, Luigi
2014-09-01
Measuring physiological dysregulation during aging could be a key tool both to understand underlying aging mechanisms and to predict clinical outcomes in patients. However, most existing indices are either circular or hard to interpret biologically. Recently, we showed that statistical distance of 14 common blood biomarkers (a measure of how strange an individual's biomarker profile is) was associated with age and mortality in the WHAS II data set, validating its use as a measure of physiological dysregulation. Here, we extend the analyses to other data sets (WHAS I and InCHIANTI) to assess the stability of the measure across populations. We found that the statistical criteria used to determine the original 14 biomarkers produced diverging results across populations; in other words, had we started with a different data set, we would have chosen a different set of markers. Nonetheless, the same 14 markers (or the subset of 12 available for InCHIANTI) produced highly similar predictions of age and mortality. We include analyses of all combinatorial subsets of the markers and show that results do not depend much on biomarker choice or data set, but that more markers produce a stronger signal. We conclude that statistical distance as a measure of physiological dysregulation is stable across populations in Europe and North America. PMID:24802990
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.
Life cycle cost analysis of aging aircraft airframe maintenance
NASA Astrophysics Data System (ADS)
Sperry, Kenneth Robert
Scope and method of study. The purpose of this study was to examine the relationship between an aircraft's age and its annual airframe maintenance costs. Common life cycle costing methodology has previously not recognized the existence of this cost growth potential, and has therefor not determined the magnitude nor significance of this cost element. This study analyzed twenty-five years of DOT Form 41-airframe maintenance cost data for the Boeing 727, 737, 747 and McDonnell Douglas DC9 and DC-10 aircraft. Statistical analysis included regression analysis, Pearson's r, and t-tests to test the null hypothesis. Findings and conclusion. Airframe maintenance cost growth was confirmed to be increasing after an aircraft's age exceeded its designed service objective of approximately twenty-years. Annual airframe maintenance cost growth increases were measured ranging from 3.5% annually for a DC-9, to approximately 9% annually for a DC-10 aircraft. Average measured coefficient of determination between age and airframe maintenance, exceeded .80, confirming a strong relationship between cost: and age. The statistical significance of the difference between airframe costs sampled in 1985, compared to airframe costs sampled in 1998 was confirmed by t-tests performed on each subject aircraft group. Future cost forecasts involving aging aircraft subjects must address cost growth due to aging when attempting to model an aircraft's economic service life.
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.
Data explorer: a prototype expert system for statistical analysis.
Aliferis, C.; Chao, E.; Cooper, G. F.
1993-01-01
The inadequate analysis of medical research data, due mainly to the unavailability of local statistical expertise, seriously jeopardizes the quality of new medical knowledge. Data Explorer is a prototype Expert System that builds on the versatility and power of existing statistical software, to provide automatic analyses and interpretation of medical data. The system draws much of its power by using belief network methods in place of more traditional, but difficult to automate, classical multivariate statistical techniques. Data Explorer identifies statistically significant relationships among variables, and using power-size analysis, belief network inference/learning and various explanatory techniques helps the user understand the importance of the findings. Finally the system can be used as a tool for the automatic development of predictive/diagnostic models from patient databases. PMID:8130501
A Statistical Analysis of the Charles F. Kettering Climate Scale.
ERIC Educational Resources Information Center
Johnson, William L.; Dixon, Paul N.
A statistical analysis was performed on the Charles F. Kettering (CFK) Scale, a popular four-section measure of school climate. The study centered on a multivariate analysis of Part A, the General Climate Factors section of the instrument, using data gathered from several elementary, junior high, and high school campuses in a large school district…
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)
Statistical analysis in dBASE-compatible databases.
Hauer-Jensen, M
1991-01-01
Database management in clinical and experimental research often requires statistical analysis of the data in addition to the usual functions for storing, organizing, manipulating and reporting. With most database systems, transfer of data to a dedicated statistics package is a relatively simple task. However, many statistics programs lack the powerful features found in database management software. dBASE IV and compatible programs are currently among the most widely used database management programs. d4STAT is a utility program for dBASE, containing a collection of statistical functions and tests for data stored in the dBASE file format. By using d4STAT, statistical calculations may be performed directly on the data stored in the database without having to exit dBASE IV or export data. Record selection and variable transformations are performed in memory, thus obviating the need for creating new variables or data files. The current version of the program contains routines for descriptive statistics, paired and unpaired t-tests, correlation, linear regression, frequency tables, Mann-Whitney U-test, Wilcoxon signed rank test, a time-saving procedure for counting observations according to user specified selection criteria, survival analysis (product limit estimate analysis, log-rank test, and graphics), and normal t and chi-squared distribution functions. PMID:2004275
Fisher statistics for analysis of diffusion tensor directional information.
Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P
2012-04-30
A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation. PMID:22342971
Proteome analysis in the assessment of ageing.
Nkuipou-Kenfack, Esther; Koeck, Thomas; Mischak, Harald; Pich, Andreas; Schanstra, Joost P; Zürbig, Petra; Schumacher, Björn
2014-11-01
Based on demographic trends, the societies in many developed countries are facing an increasing number and proportion of people over the age of 65. The raise in elderly populations along with improved health-care will be concomitant with an increased prevalence of ageing-associated chronic conditions like cardiovascular, renal, and respiratory diseases, arthritis, dementia, and diabetes mellitus. This is expected to pose unprecedented challenges both for individuals and societies and their health care systems. An ultimate goal of ageing research is therefore the understanding of physiological ageing and the achievement of 'healthy' ageing by decreasing age-related pathologies. However, on a molecular level, ageing is a complex multi-mechanistic process whose contributing factors may vary individually, partly overlap with pathological alterations, and are often poorly understood. Proteome analysis potentially allows modelling of these multifactorial processes. This review summarises recent proteomic research on age-related changes identified in animal models and human studies. We combined this information with pathway analysis to identify molecular mechanisms associated with ageing. We identified some molecular pathways that are affected in most or even all organs and others that are organ-specific. However, appropriately powered studies are needed to confirm these findings based in in silico evaluation. PMID:25257180
Adaptive Strategy for the Statistical Analysis of Connectomes
Meskaldji, Djalel Eddine; Ottet, Marie-Christine; Cammoun, Leila; Hagmann, Patric; Meuli, Reto; Eliez, Stephan; Thiran, Jean Philippe; Morgenthaler, Stephan
2011-01-01
We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores. PMID:21829681
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.
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
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.
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.
Revisiting the statistical analysis of pyroclast density and porosity data
NASA Astrophysics Data System (ADS)
Bernard, B.; Kueppers, U.; Ortiz, H.
2015-07-01
Explosive volcanic eruptions are commonly characterized based on a thorough analysis of the generated deposits. Amongst other characteristics in physical volcanology, density and porosity of juvenile clasts are some of the most frequently used to constrain eruptive dynamics. In this study, we evaluate the sensitivity of density and porosity data to statistical methods and introduce a weighting parameter to correct issues raised by the use of frequency analysis. Results of textural investigation can be biased by clast selection. Using statistical tools as presented here, the meaningfulness of a conclusion can be checked for any data set easily. This is necessary to define whether or not a sample has met the requirements for statistical relevance, i.e. whether a data set is large enough to allow for reproducible results. Graphical statistics are used to describe density and porosity distributions, similar to those used for grain-size analysis. This approach helps with the interpretation of volcanic deposits. To illustrate this methodology, we chose two large data sets: (1) directed blast deposits of the 3640-3510 BC eruption of Chachimbiro volcano (Ecuador) and (2) block-and-ash-flow deposits of the 1990-1995 eruption of Unzen volcano (Japan). We propose the incorporation of this analysis into future investigations to check the objectivity of results achieved by different working groups and guarantee the meaningfulness of the interpretation.
NASA Astrophysics Data System (ADS)
Salih, A. L.; Mühlbauer, M.; Grumpe, A.; Pasckert, J. H.; Wöhler, C.; Hiesinger, H.
2016-06-01
The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher
Statistical inference for exploratory data analysis and model diagnostics.
Buja, Andreas; Cook, Dianne; Hofmann, Heike; Lawrence, Michael; Lee, Eun-Kyung; Swayne, Deborah F; Wickham, Hadley
2009-11-13
We propose to furnish visual statistical methods with an inferential framework and protocol, modelled on confirmatory statistical testing. In this framework, plots take on the role of test statistics, and human cognition the role of statistical tests. Statistical significance of 'discoveries' is measured by having the human viewer compare the plot of the real dataset with collections of plots of simulated datasets. A simple but rigorous protocol that provides inferential validity is modelled after the 'lineup' popular from criminal legal procedures. Another protocol modelled after the 'Rorschach' inkblot test, well known from (pop-)psychology, will help analysts acclimatize to random variability before being exposed to the plot of the real data. The proposed protocols will be useful for exploratory data analysis, with reference datasets simulated by using a null assumption that structure is absent. The framework is also useful for model diagnostics in which case reference datasets are simulated from the model in question. This latter point follows up on previous proposals. Adopting the protocols will mean an adjustment in working procedures for data analysts, adding more rigour, and teachers might find that incorporating these protocols into the curriculum improves their students' statistical thinking. PMID:19805449
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 of 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
Statistical Software for spatial analysis of stratigraphic data sets
Energy Science and Technology Software Center (ESTSC)
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
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.
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.
A novel statistical analysis and interpretation of flow cytometry data
Banks, H.T.; Kapraun, D.F.; Thompson, W. Clayton; Peligero, Cristina; Argilaguet, Jordi; Meyerhans, Andreas
2013-01-01
A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+ T and CD8+ T cells collected from two healthy donors. This novel mathematical and statistical framework is shown to form the basis for accurate, meaningful analysis of cellular behaviour for a population of cells labelled with the dye carboxyfluorescein succinimidyl ester and stimulated to divide. PMID:23826744
Hayashi, C
1986-04-01
The subjects which are often encountered in the statistical design and analysis of data in medical science studies were discussed. The five topics examined were: Medical science and statistical methods So-called mathematical statistics and medical science Fundamentals of cross-tabulation analysis of statistical data and inference Exploratory study by multidimensional data analyses Optimal process control of individual, medical science and informatics of statistical data In I, the author's statistico-mathematical idea is characterized as the analysis of phenomena by statistical data. This is closely related to the logic, methodology and philosophy of science. This statistical concept and method are based on operational and pragmatic ideas. Self-examination of mathematical statistics is particularly focused in II and III. In II, the effectiveness of experimental design and statistical testing is thoroughly examined with regard to the study of medical science, and the limitation of its application is discussed. In III the apparent paradox of analysis of cross-tabulation of statistical data and statistical inference is shown. This is due to the operation of a simple two- or three-fold cross-tabulation analysis of (more than two or three) multidimensional data, apart from the sophisticated statistical test theory of association. In IV, the necessity of informatics of multidimensional data analysis in medical science is stressed. In V, the following point is discussed. The essential point of clinical trials is that they are not based on any simple statistical test in a traditional experimental design but on the optimal process control of individuals in the information space of the body and mind, which is based on a knowledge of medical science and the informatics of multidimensional statistical data analysis. PMID:3729436
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
2010-01-01
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.
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
Feature-based statistical analysis of combustion simulation data.
Bennett, Janine C; Krishnamoorthy, Vaidyanathan; Liu, Shusen; Grout, Ray W; Hawkes, Evatt R; Chen, Jacqueline H; Shepherd, Jason; Pascucci, Valerio; Bremer, Peer-Timo
2011-12-01
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
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
Statistic analyses of the color experience according to the age of the observer.
Hunjet, Anica; Parac-Osterman, Durdica; Vucaj, Edita
2013-04-01
Psychological experience of color is a real state of the communication between the environment and color, and it will depend on the source of the light, angle of the view, and particular on the observer and his health condition. Hering's theory or a theory of the opponent processes supposes that cones, which are situated in the retina of the eye, are not sensible on the three chromatic domains (areas, fields, zones) (red, green and purple-blue), but they produce a signal based on the principle of the opposed pairs of colors. A reason of this theory depends on the fact that certain disorders of the color eyesight, which include blindness to certain colors, cause blindness to pairs of opponent colors. This paper presents a demonstration of the experience of blue and yellow tone according to the age of the observer. For the testing of the statistically significant differences in the omission in the color experience according to the color of the background we use following statistical tests: Mann-Whitnney U Test, Kruskal-Wallis ANOVA and Median test. It was proven that the differences are statistically significant in the elderly persons (older than 35 years). PMID:23837226
SPA- STATISTICAL PACKAGE FOR TIME AND FREQUENCY DOMAIN ANALYSIS
NASA Technical Reports Server (NTRS)
Brownlow, J. D.
1994-01-01
The need for statistical analysis often arises when data is in the form of a time series. This type of data is usually a collection of numerical observations made at specified time intervals. Two kinds of analysis may be performed on the data. First, the time series may be treated as a set of independent observations using a time domain analysis to derive the usual statistical properties including the mean, variance, and distribution form. Secondly, the order and time intervals of the observations may be used in a frequency domain analysis to examine the time series for periodicities. In almost all practical applications, the collected data is actually a mixture of the desired signal and a noise signal which is collected over a finite time period with a finite precision. Therefore, any statistical calculations and analyses are actually estimates. The Spectrum Analysis (SPA) program was developed to perform a wide range of statistical estimation functions. SPA can provide the data analyst with a rigorous tool for performing time and frequency domain studies. In a time domain statistical analysis the SPA program will compute the mean variance, standard deviation, mean square, and root mean square. It also lists the data maximum, data minimum, and the number of observations included in the sample. In addition, a histogram of the time domain data is generated, a normal curve is fit to the histogram, and a goodness-of-fit test is performed. These time domain calculations may be performed on both raw and filtered data. For a frequency domain statistical analysis the SPA program computes the power spectrum, cross spectrum, coherence, phase angle, amplitude ratio, and transfer function. The estimates of the frequency domain parameters may be smoothed with the use of Hann-Tukey, Hamming, Barlett, or moving average windows. Various digital filters are available to isolate data frequency components. Frequency components with periods longer than the data collection interval
Statistical analysis of high density diffuse optical tomography
Hassanpour, Mahlega S.; White, Brian R.; Eggebrecht, Adam T.; Ferradal, Silvina L.; Snyder, Abraham Z.; Culver, Joseph P.
2014-01-01
High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD- DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci. PMID:23732886
HistFitter - A flexible framework for statistical data analysis
NASA Astrophysics Data System (ADS)
Lorenz, J. M.; Baak, M.; Besjes, G. J.; Côté, D.; Koutsman, A.; Short, D.
2015-05-01
We present a software framework for statistical data analysis, called HistFitter, that has extensively been used 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. The key innovations of HistFitter are to weave the concepts of control, validation and signal regions into its very fabric, and to treat them with rigorous statistical methods, while providing multiple tools to visualize and interpret the results through a simple configuration interface.
1993-02-01
In 1984, 99% of abortions conducted in Bombay, India, were of female fetuses. In 1986-87, 30,000-50,000 female fetuses were aborted in India. In 1987-88, 7 Delhi clinics conducted 13,000 sex determination tests. Thus, discrimination against females begins before birth in India. Some states (Maharashtra, Goa, and Gujarat) have drafted legislation to prevent the use of prenatal diagnostic tests (e.g., ultrasonography) for sex determination purposes. Families make decisions about an infant's nutrition based on the infant's sex so it is not surprising to see a higher incidence of morbidity among girls than boys (e.g., for respiratory infections in 1985, 55.5% vs. 27.3%). Consequently, they are more likely to die than boys. Even though vasectomy is simpler and safer than tubectomy, the government promotes female sterilizations. The percentage of all sexual sterilizations being tubectomy has increased steadily from 84% to 94% (1986-90). Family planning programs focus on female contraceptive methods, despite the higher incidence of adverse health effects from female methods (e.g., IUD causes pain and heavy bleeding). Some women advocates believe the effects to be so great that India should ban contraceptives and injectable contraceptives. The maternal mortality rate is quite high (460/100,000 live births), equaling a lifetime risk of 1:18 of a pregnancy-related death. 70% of these maternal deaths are preventable. Leading causes of maternal deaths in India are anemia, hemorrhage, eclampsia, sepsis, and abortion. Most pregnant women do not receive prenatal care. Untrained personnel attend about 70% of deliveries in rural areas and 29% in urban areas. Appropriate health services and other interventions would prevent the higher age specific death rates for females between 0 and 35 years old. Even though the government does provide maternal and child health services, it needs to stop decreasing resource allocate for health and start increasing it. PMID:12286355
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 . PMID:27248514
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
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.
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
NASA Astrophysics Data System (ADS)
Al-Obaisi, A. M.; El-Danaf, E. A.; Ragab, A. E.; Soliman, M. S.
2016-04-01
The addition of Ag to Al-Cu-Mg systems has been proposed to replace the existing high-strength 2xxx and 7xxx Al alloys. The aged Al-Cu-Mg-Ag alloys exhibited promising properties, due to special type of precipitates named Ω, which cooperate with other precipitates to enhance the mechanical properties significantly. In the present investigation, the effect of changing percentages of alloying elements, aging time, and aging temperature on the hardness values was studied based on a factorial design. According to this design of experiments (DOE)—23 factorial design, eight alloys were cast and hot rolled, where (Cu, Mg, and Ag) were added to aluminum with two different levels for each alloying element. These alloys were aged at different temperatures (160, 190, and 220 °C) over a wide range of time intervals from 10 min. to 64 h. The resulting hardness data were used as an input for Minitab software to model and relate the process variables with hardness through a regression analysis. Modifying the alloying elements' weight percentages to the high level enhanced the hardness of the alloy with about 40% as compared to the alloy containing the low level of all alloying elements. Through analysis of variance (ANOVA), it was figured out that altering the fraction of Cu had the greatest effect on the hardness values with a contribution of about 49%. Also, second-level interaction terms had about 21% of impact on the hardness values. Aging time, quadratic terms, and third-level interaction terms had almost the same level of influence on hardness values (about 10% contribution). Furthermore, the results have shown that small addition of Mg and Ag was enough to improve the mechanical properties of the alloy significantly. The statistical model formulated interpreted about 80% of the variation in hardness values.
NASA Astrophysics Data System (ADS)
Al-Obaisi, A. M.; El-Danaf, E. A.; Ragab, A. E.; Soliman, M. S.
2016-06-01
The addition of Ag to Al-Cu-Mg systems has been proposed to replace the existing high-strength 2xxx and 7xxx Al alloys. The aged Al-Cu-Mg-Ag alloys exhibited promising properties, due to special type of precipitates named Ω, which cooperate with other precipitates to enhance the mechanical properties significantly. In the present investigation, the effect of changing percentages of alloying elements, aging time, and aging temperature on the hardness values was studied based on a factorial design. According to this design of experiments (DOE)—23 factorial design, eight alloys were cast and hot rolled, where (Cu, Mg, and Ag) were added to aluminum with two different levels for each alloying element. These alloys were aged at different temperatures (160, 190, and 220 °C) over a wide range of time intervals from 10 min. to 64 h. The resulting hardness data were used as an input for Minitab software to model and relate the process variables with hardness through a regression analysis. Modifying the alloying elements' weight percentages to the high level enhanced the hardness of the alloy with about 40% as compared to the alloy containing the low level of all alloying elements. Through analysis of variance (ANOVA), it was figured out that altering the fraction of Cu had the greatest effect on the hardness values with a contribution of about 49%. Also, second-level interaction terms had about 21% of impact on the hardness values. Aging time, quadratic terms, and third-level interaction terms had almost the same level of influence on hardness values (about 10% contribution). Furthermore, the results have shown that small addition of Mg and Ag was enough to improve the mechanical properties of the alloy significantly. The statistical model formulated interpreted about 80% of the variation in hardness values.
Revisiting the statistical analysis of pyroclast density and porosity data
NASA Astrophysics Data System (ADS)
Bernard, B.; Kueppers, U.; Ortiz, H.
2015-03-01
Explosive volcanic eruptions are commonly characterized based on a thorough analysis of the generated deposits. Amongst other characteristics in physical volcanology, density and porosity of juvenile clasts are some of the most frequently used characteristics to constrain eruptive dynamics. In this study, we evaluate the sensitivity of density and porosity data and introduce a weighting parameter to correct issues raised by the use of frequency analysis. Results of textural investigation can be biased by clast selection. Using statistical tools as presented here, the meaningfulness of a conclusion can be checked for any dataset easily. This is necessary to define whether or not a sample has met the requirements for statistical relevance, i.e. whether a dataset is large enough to allow for reproducible results. Graphical statistics are used to describe density and porosity distributions, similar to those used for grain-size analysis. This approach helps with the interpretation of volcanic deposits. To illustrate this methodology we chose two large datasets: (1) directed blast deposits of the 3640-3510 BC eruption of Chachimbiro volcano (Ecuador) and (2) block-and-ash-flow deposits of the 1990-1995 eruption of Unzen volcano (Japan). We propose add the use of this analysis for future investigations to check the objectivity of results achieved by different working groups and guarantee the meaningfulness of the interpretation.
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. PMID:22649482
Statistical Analysis of the Heavy Neutral Atoms Measured by IBEX
NASA Astrophysics Data System (ADS)
Park, Jeewoo; Kucharek, Harald; Möbius, Eberhard; Galli, André; Livadiotis, George; Fuselier, Steve A.; McComas, David J.
2015-10-01
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&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&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.
Chung, Moo K; Kim, Seung-Goo; Schaefer, Stacey M; van Reekum, Carien M; Peschke-Schmitz, Lara; Sutterer, Matthew J; Davidson, Richard J
2014-03-21
The sparse regression framework has been widely used in medical image processing and analysis. However, it has been rarely used in anatomical studies. We present a sparse shape modeling framework using the Laplace-Beltrami (LB) eigenfunctions of the underlying shape and show its improvement of statistical power. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes as a form of Fourier descriptors. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we present a LB-based method to filter out only the significant eigenfunctions by imposing a sparse penalty. For dense anatomical data such as deformation fields on a surface mesh, the sparse regression behaves like a smoothing process, which will reduce the error of incorrectly detecting false negatives. Hence the statistical power improves. The sparse shape model is then applied in investigating the influence of age on amygdala and hippocampus shapes in the normal population. The advantage of the LB sparse framework is demonstrated by showing the increased statistical power. PMID:25302007
Statistical analysis of spectral data for vegetation detection
NASA Astrophysics Data System (ADS)
Love, Rafael; Cathcart, J. Michael
2006-05-01
Identification and reduction of false alarms provide a critical component in the detection of landmines. Research at Georgia Tech over the past several years has focused on this problem through an examination of the signature characteristics of various background materials. These efforts seek to understand the physical basis and features of these signatures as an aid to the development of false target identification techniques. The investigation presented in this paper deal concentrated on the detection of foliage in long wave infrared imagery. Data collected by a hyperspectral long-wave infrared sensor provided the background signatures used in this study. These studies focused on an analysis of the statistical characteristics of both the intensity signature and derived emissivity data. Results from these studies indicate foliage signatures possess unique characteristics that can be exploited to enable detection of vegetation in LWIR images. This paper will present review of the approach and results of the statistical analysis.
Statistical analysis of mineral soils in the Odra valley
NASA Astrophysics Data System (ADS)
Hudak, Magda; Rojna, Arkadiusz
2012-10-01
The aim of this article is to present the results of statistical analyses of laboratory experiment results obtained from an ITB ZW-K2 apparatus, Kamieński tubes and grain-size distribution curves. Beside basic statistical parameters (mean, sum, minimum and maximum), correlation analysis and multivariate analysis of variance at significance levels α < 0.01 and α < 0.05 were taken into account, as well as calculations of LSD confidence half-intervals. The research material was collected from the valley of the Odra river near the town of Słubice in Lubuskie province. The research involved mineral, non-rock fine-grained, non-cohesive soils lying at the depth of 0.3-1.5 m.
A statistical analysis of mesoscale rainfall as a random cascade
NASA Technical Reports Server (NTRS)
Gupta, Vijay K.; Waymire, Edward C.
1993-01-01
The paper considers the random cascade theory for spatial rainfall. Particular attention was given to the following four areas: (1) the relationship of the random cascade theory of rainfall to the simple scaling and the hierarchical cluster-point-process theories, (2) the mathematical foundations for some of the formalisms commonly applied in the develpment of statistical cascade theory, (3) the empirical evidence for a random cascade theory of rainfall, and (4) the way of using data for making estimates of parameters and for making statistical inference within this theoretical framework. An analysis of space-time rainfall data is presented. Cascade simulations are carried out to provide a comparison with methods of analysis that are applied to the rainfall data.
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.
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.
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.; Krauss, T. F.; Fratalocchi, A.
2012-04-30
In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.
Statistical sampling analysis for stratospheric measurements from satellite missions
NASA Technical Reports Server (NTRS)
Drewry, J. W.; Harrison, E. F.; Brooks, D. R.; Robbins, J. L.
1978-01-01
Earth orbiting satellite experiments can be designed to measure stratospheric constituents such as ozone by utilizing remote sensing techniques. Statistical analysis techniques, mission simulation and model development have been utilized to develop a method for analyzing various mission/sensor combinations. Existing and planned NASA satellite missions such as Nimbus-4 and G, and Stratospheric Aerosol and Gas Experiment-Application Explorer Mission (SAGE-AEM) have been analyzed to determine the ability of the missions to adequately sample the global field.
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
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
Statistical Analysis of Longitudinal Psychiatric Data with Dropouts
Mazumdar, Sati; Tang, Gong; Houck, Patricia R.; Dew, Mary Amanda; Begley, Amy E.; Scott, John; Mulsant, Benoit H.; Reynolds, Charles F.
2007-01-01
Longitudinal studies are used in psychiatric research to address outcome changes over time within and between individuals. However, because participants may drop out of a study prematurely, ignoring the nature of dropout often leads to biased inference, and in turn, wrongful conclusions. The purpose of the present paper is: (1) to review several dropout processes, corresponding inferential issues and recent methodological advances; (2) to evaluate the impact of assumptions regarding the dropout processes on inference by simulation studies and an illustrative example using psychiatric data; and (3) to provide a general strategy for practitioners to perform analyses of longitudinal data with dropouts, using software available commercially or in the public domain. The statistical methods used in this paper are maximum likelihood, multiple imputation and semi-parametric regression methods for inference, as well as Little’s test and ISNI (Index of Sensitivity to Nonignorability) for assessing statistical dropout mechanisms. We show that accounting for the nature of the dropout process influences results and that sensitivity analysis is useful in assessing the robustness of parameter estimates and related uncertainties. We conclude that recording the causes of dropouts should be an integral part of any statistical analysis with longitudinal psychiatric data, and we recommend performing a sensitivity analysis when the exact nature of the dropout process cannot be discerned. PMID:17092516
Lao, Yi; Kang, Yue; Collignon, Olivier; Brun, Caroline; Kheibai, Shadi B; Alary, Flamine; Gee, James; Nelson, Marvin D; Lepore, Franco; Lepore, Natasha
2015-12-16
Early blind individuals are known to exhibit structural brain reorganization. Particularly, early-onset blindness may trigger profound brain alterations that affect not only the visual system but also the remaining sensory systems. Diffusion tensor imaging (DTI) allows in-vivo visualization of brain white matter connectivity, and has been extensively used to study brain white matter structure. Among statistical approaches based on DTI, tract-based spatial statistics (TBSS) is widely used because of its ability to automatically perform whole brain white matter studies. Tract specific analysis (TSA) is a more recent method that localizes changes in specific white matter bundles. In the present study, we compare TBSS and TSA results of DTI scans from 12 early blind individuals and 13 age-matched sighted controls, with two aims: (a) to investigate white matter alterations associated with early visual deprivation; (b) to examine the relative sensitivity of TSA when compared with TBSS, for both deficit and hypertrophy of white matter microstructures. Both methods give consistent results for broad white matter regions of deficits. However, TBSS does not detect hypertrophy of white matter, whereas TSA shows a higher sensitivity in detecting subtle differences in white matter colocalized to the posterior parietal lobe. PMID:26559727
Spectral Analysis of B Stars: An Application of Bayesian Statistics
NASA Astrophysics Data System (ADS)
Mugnes, J.-M.; Robert, C.
2012-12-01
To better understand the processes involved in stellar physics, it is necessary to obtain accurate stellar parameters (effective temperature, surface gravity, abundances…). Spectral analysis is a powerful tool for investigating stars, but it is also vital to reduce uncertainties at a decent computational cost. Here we present a spectral analysis method based on a combination of Bayesian statistics and grids of synthetic spectra obtained with TLUSTY. This method simultaneously constrains the stellar parameters by using all the lines accessible in observed spectra and thus greatly reduces uncertainties and improves the overall spectrum fitting. Preliminary results are shown using spectra from the Observatoire du Mont-Mégantic.
A statistical analysis of sea temperature data. A statistical analysis of sea temperature data
NASA Astrophysics Data System (ADS)
Lorentzen, Torbjørn
2015-02-01
The paper analyzes sea temperature series measured at two geographical locations along the coast of Norway. We address the question whether the series are stable over the sample period 1936-2012 and whether we can measure any signal of climate change in the regional data. We use nonstandard supF, OLS-based CUSUM, RE, and Chow tests in combination with the Bai-Perron's structural break test to identify potential changes in the temperature. The augmented Dickey-Fuller, the KPSS, and the nonparametric Phillips-Perron tests are in addition applied in the evaluation of the stochastic properties of the series. The analysis indicates that both series undergo similar structural instabilities in the form of small shifts in the temperature level. The temperature at Lista (58° 06' N, 06° 38' E) shifts downward about 1962 while the Skrova series (68° 12' N, 14° 10' E) shifts to a lower level about 1977. Both series shift upward about 1987, and after a period of increasing temperature, both series start leveling off about the turn of the millennium. The series have no significant stochastic or deterministic trend. The analysis indicates that the mean temperature has moved upward in decadal, small steps since the 1980s. The result is in accordance with recent analyses of sea temperatures in the North Atlantic. The findings are also related to the so-called hiatus phenomenon where natural variation in climate can mask global warming processes. The paper contributes to the discussion of applying objective methods in measuring climate change.
A Laboratory Exercise in Statistical Analysis of Data
NASA Astrophysics Data System (ADS)
Vitha, Mark F.; Carr, Peter W.
1997-08-01
An undergraduate laboratory exercise in statistical analysis of data has been developed based on facile weighings of vitamin E pills. The use of electronic top-loading balances allows for very rapid data collection. Therefore, students obtain a sufficiently large number of replicates to provide statistically meaningful data sets. Through this exercise, students explore the effects of sample size and different types of sample averaging on the standard deviation of the average weight per pill. An emphasis is placed on the difference between the standard deviation of the mean and the standard deviation of the population. Students also perform the Q-test and t-test and are introduced to the X2-test. In this report, the class data from two consecutive offerings of the course are compared and reveal a statistically significant increase in the average weight per pill, presumably due to the absorption of water over time. Histograms of the class data are shown and used to illustrate the importance of plotting the data. Overall, through this brief laboratory exercise, students are exposed to many important statistical tests and concepts which are then used and further developed throughout the remainder of the course.
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.
Region-based Statistical Analysis of 2D PAGE Images
Li, Feng; Seillier-Moiseiwitsch, Françoise; Korostyshevskiy, Valeriy R.
2011-01-01
A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini-Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is shown by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images. PMID:21850152
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.
Crow, C.J.
1985-01-01
Middle Ordovician age Chickamauga Group carbonates crop out along the Birmingham and Murphrees Valley anticlines in central Alabama. The macrofossil contents on exposed surfaces of seven bioherms have been counted to determine their various paleontologic characteristics. Twelve groups of organisms are present in these bioherms. Dominant organisms include bryozoans, algae, brachiopods, sponges, pelmatozoans, stromatoporoids and corals. Minor accessory fauna include predators, scavengers and grazers such as gastropods, ostracods, trilobites, cephalopods and pelecypods. Vertical and horizontal niche zonation has been detected for some of the bioherm dwelling fauna. No one bioherm of those studied exhibits all 12 groups of organisms; rather, individual bioherms display various subsets of the total diversity. Statistical treatment (G-test) of the diversity data indicates a lack of statistical homogeneity of the bioherms, both within and between localities. Between-locality population heterogeneity can be ascribed to differences in biologic responses to such gross environmental factors as water depth and clarity, and energy levels. At any one locality, gross aspects of the paleoenvironments are assumed to have been more uniform. Significant differences among bioherms at any one locality may have resulted from patchy distribution of species populations, differential preservation and other factors.
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).
Bayes Method Plant Aging Risk Analysis
Energy Science and Technology Software Center (ESTSC)
1992-03-13
DORIAN is an integrated package for performing Bayesian aging analysis of reliability data; e.g. for identifying trends in component failure rates and/or outage durations as a function of time. The user must specify several alternatives hypothesized aging models (i.e. possible trends) along with prior probabilities indicating the subjective probability that each trend is actually the correct one. DORIAN then uses component failure and/or repair data over time to update these prior probabilities and develop amore » posterior probability for each aging model, representing the probability that each model is the correct one in light of the observed data rather than a priori. Mean, median, and 5th and 95th percentile trends are also compiled from the posterior probabilities.« less
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. PMID:26699457
Statistical wind analysis for near-space applications
NASA Astrophysics Data System (ADS)
Roney, Jason A.
2007-09-01
Statistical wind models were developed based on the existing observational wind data for near-space altitudes between 60 000 and 100 000 ft (18 30 km) above ground level (AGL) at two locations, Akon, OH, USA, and White Sands, NM, USA. These two sites are envisioned as playing a crucial role in the first flights of high-altitude airships. The analysis shown in this paper has not been previously applied to this region of the stratosphere for such an application. Standard statistics were compiled for these data such as mean, median, maximum wind speed, and standard deviation, and the data were modeled with Weibull distributions. These statistics indicated, on a yearly average, there is a lull or a “knee” in the wind between 65 000 and 72 000 ft AGL (20 22 km). From the standard statistics, trends at both locations indicated substantial seasonal variation in the mean wind speed at these heights. The yearly and monthly statistical modeling indicated that Weibull distributions were a reasonable model for the data. Forecasts and hindcasts were done by using a Weibull model based on 2004 data and comparing the model with the 2003 and 2005 data. The 2004 distribution was also a reasonable model for these years. Lastly, the Weibull distribution and cumulative function were used to predict the 50%, 95%, and 99% winds, which are directly related to the expected power requirements of a near-space station-keeping airship. These values indicated that using only the standard deviation of the mean may underestimate the operational conditions.
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 nanoparticle dosing in a dynamic cellular system
NASA Astrophysics Data System (ADS)
Summers, Huw D.; Rees, Paul; Holton, Mark D.; Rowan Brown, M.; Chappell, Sally C.; Smith, Paul J.; Errington, Rachel J.
2011-03-01
The delivery of nanoparticles into cells is important in therapeutic applications and in nanotoxicology. Nanoparticles are generally targeted to receptors on the surfaces of cells and internalized into endosomes by endocytosis, but the kinetics of the process and the way in which cell division redistributes the particles remain unclear. Here we show that the chance of success or failure of nanoparticle uptake and inheritance is random. Statistical analysis of nanoparticle-loaded endosomes indicates that particle capture is described by an over-dispersed Poisson probability distribution that is consistent with heterogeneous adsorption and internalization. Partitioning of nanoparticles in cell division is random and asymmetric, following a binomial distribution with mean probability of 0.52-0.72. These results show that cellular targeting of nanoparticles is inherently imprecise due to the randomness of nature at the molecular scale, and the statistical framework offers a way to predict nanoparticle dosage for therapy and for the study of nanotoxins.
Statistical analysis of the particulation of shaped charge jets
Minich, R W, Baker, E L; Schwartz, A J
1999-08-12
A statistical analysis of shaped charge jet break-up was carried out in order to investigate the role of nonlinear instabilities leading to the particulation of the jet. Statistical methods generally used for studying fluctuations in nonlinear dynamical systems are applied to experimentally measured velocities of the individual particles. In particular we present results suggesting the deviation of non-Gaussian behavior for interparticle velocity correlations, characteristic of nonlinear dynamical systems. Results are presented for two silver shaped charge jets that differ primarily in their material processing. We provide evidence that the particulation of a jet is not random, but has its origin in a deterministic dynamical process involving the nonlinear coupling of two oscillators analogous to the underling dynamics observed in Rayleigh-Benard convection and modeled in the return map of Curry and Yorke.
A Statistical Analysis of Lunisolar-Earthquake Connections
NASA Astrophysics Data System (ADS)
Rüegg, Christian Michael-André
2012-11-01
Despite over a century of study, the relationship between lunar cycles and earthquakes remains controversial and difficult to quantitatively investigate. Perhaps as a consequence, major earthquakes around the globe are frequently followed by "prediction claim", using lunar cycles, that generate media furore and pressure scientists to provide resolute answers. The 2010-2011 Canterbury earthquakes in New Zealand were no exception; significant media attention was given to lunar derived earthquake predictions by non-scientists, even though the predictions were merely "opinions" and were not based on any statistically robust temporal or causal relationships. This thesis provides a framework for studying lunisolar earthquake temporal relationships by developing replicable statistical methodology based on peer reviewed literature. Notable in the methodology is a high accuracy ephemeris, called ECLPSE, designed specifically by the author for use on earthquake catalogs and a model for performing phase angle analysis.
Statistical analysis of effective singular values in matrix rank determination
NASA Technical Reports Server (NTRS)
Konstantinides, Konstantinos; Yao, Kung
1988-01-01
A major problem in using SVD (singular-value decomposition) as a tool in determining the effective rank of a perturbed matrix is that of distinguishing between significantly small and significantly large singular values to the end, conference regions are derived for the perturbed singular values of matrices with noisy observation data. The analysis is based on the theories of perturbations of singular values and statistical significance test. Threshold bounds for perturbation due to finite-precision and i.i.d. random models are evaluated. In random models, the threshold bounds depend on the dimension of the matrix, the noisy variance, and predefined statistical level of significance. Results applied to the problem of determining the effective order of a linear autoregressive system from the approximate rank of a sample autocorrelation matrix are considered. Various numerical examples illustrating the usefulness of these bounds and comparisons to other previously known approaches are given.
Statistical analysis of nanoparticle dosing in a dynamic cellular system.
Summers, Huw D; Rees, Paul; Holton, Mark D; Brown, M Rowan; Chappell, Sally C; Smith, Paul J; Errington, Rachel J
2011-03-01
The delivery of nanoparticles into cells is important in therapeutic applications and in nanotoxicology. Nanoparticles are generally targeted to receptors on the surfaces of cells and internalized into endosomes by endocytosis, but the kinetics of the process and the way in which cell division redistributes the particles remain unclear. Here we show that the chance of success or failure of nanoparticle uptake and inheritance is random. Statistical analysis of nanoparticle-loaded endosomes indicates that particle capture is described by an over-dispersed Poisson probability distribution that is consistent with heterogeneous adsorption and internalization. Partitioning of nanoparticles in cell division is random and asymmetric, following a binomial distribution with mean probability of 0.52-0.72. These results show that cellular targeting of nanoparticles is inherently imprecise due to the randomness of nature at the molecular scale, and the statistical framework offers a way to predict nanoparticle dosage for therapy and for the study of nanotoxins. PMID:21258333
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 Mechanics Analysis of ATP Binding to a Multisubunit Enzyme
NASA Astrophysics Data System (ADS)
Zhang, Yun-Xin
2014-10-01
Due to inter-subunit communication, multisubunit enzymes usually hydrolyze ATP in a concerted fashion. However, so far the principle of this process remains poorly understood. In this study, from the viewpoint of statistical mechanics, a simple model is presented. In this model, we assume that the binding of ATP will change the potential of the corresponding enzyme subunit, and the degree of this change depends on the state of its adjacent subunits. The probability of enzyme in a given state satisfies the Boltzmann's distribution. Although it looks much simple, this model can fit the recent experimental data of chaperonin TRiC/CCT well. From this model, the dominant state of TRiC/CCT can be obtained. This study provide a new way to understand biophysical processe by statistical mechanics analysis.
Statistical analysis of the modal properties of large structural systems.
NASA Technical Reports Server (NTRS)
Collins, J. D.; Kennedy, B.; Hart, G. C.
1971-01-01
A theory is developed to predict eigenvalue and eigenvector uncertainty in large dynamic models. The uncertainty is based on physical property uncertainty and should not be confused with numerical roundoff, although the method can be extended to include the latter. The theory, when implemented on a computer, is used to analyze the uncertainties in frequencies and mode shapes based on uncertainties in mass, stiffness, modulus of elasticity, etc. The method incorporates a linear statistical model which is quite adequate for handling property uncertainties of 10% or more. The model is not limited to small systems but uses certain statistical assumptions as well as selective matrix manipulations to keep the size of all matrix operations to within the number of degrees of freedom of the system. Examples are given for two longitudinal vibration problems, and the results are supported by a Monte Carlo analysis.
Statistical Analysis of Human Blood Cytometries: Potential Donors and Patients
NASA Astrophysics Data System (ADS)
Bernal-Alvarado, J.; Segovia-Olvera, P.; Mancilla-Escobar, B. E.; Palomares, P.
2004-09-01
The histograms of the cell volume from human blood present valuable information for clinical evaluation. Measurements can be performed with automatic equipment and a graphical presentation of the data is available, nevertheless, an statistical and mathematical analysis of the cell volume distribution could be useful for medical interpretation too, as much as the numerical parameters characterizing the histograms might be correlated with healthy people and patient populations. In this work, a statistical exercise was performed in order to find the most suitable model fitting the cell volume histograms. Several trial functions were tested and their parameters were tabulated. Healthy people exhibited an average of the cell volume of 85 femto liters while patients had 95 femto liters. White blood cell presented a small variation and platelets preserved their average for both populations.
The Effects of Statistical Analysis Software and Calculators on Statistics Achievement
ERIC Educational Resources Information Center
Christmann, Edwin P.
2009-01-01
This study compared the effects of microcomputer-based statistical software and hand-held calculators on the statistics achievement of university males and females. The subjects, 73 graduate students enrolled in univariate statistics classes at a public comprehensive university, were randomly assigned to groups that used either microcomputer-based…
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.
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).
a Multivariate Statistical Analysis of Visibility at California Regions.
NASA Astrophysics Data System (ADS)
Motallebi, Nehzat
This study summarizes the results of a comprehensive study of visibility in California. California is one of the few states that has promulgated air quality standards for visibility. The study was concerned not only with major metropolitan areas such as Los Angeles, but also with deterioration of visibility in the less urbanized areas of California. The relationships among visibility reduction, atmospheric pollutants, and meteorological conditions were examined by using the multivariate statistical techniques of principal component analysis and multiple linear regression analysis. The primary concern of this work was to find which of the many atmospheric constituents most effectively reduce visibility, and to determine the role of the different meteorological variables on these relationships. Another objective was to identify the major pollutant sources and transport routes which contribute to visibility degradation. In order to establish the relationship between the light scattering coefficient and particulate data, both the size distribution and the elemental composition of particulate aerosols were considered. Meanwhile, including meteorological parameters in the principal component analysis made it possible to investigate meteorological effects on the observed pollution patterns. The associations among wind direction, elemental concentration, and additional meteorological parameters were considered by using a special modification of principal component analysis. This technique can identify all of the main features, and provides reasonable source direction for particular elements. It is appropriate to note that there appeared to be no published accounts of a principal component analysis for a data set similar to that analyzed in this work. Finally, the results of the multivariate statistical analyses, multiple linear regression analysis and principal component analysis, indicate that intermediate size sulfur containing aerosols, sulfur size mode 0.6 (mu)m < D
Statistical analysis of static shape control in space structures
NASA Technical Reports Server (NTRS)
Burdisso, Ricardo A.; Haftka, Raphael T.
1990-01-01
The article addresses the problem of efficient analysis of the statistics of initial and corrected shape distortions in space structures. Two approaches for improving efficiency are considered. One is an adjoint technique for calculating distortion shapes: the second is a modal expansion of distortion shapes in terms of pseudo-vibration modes. The two techniques are applied to the problem of optimizing actuator locations on a 55 m radiometer antenna. The adjoint analysis technique is used with a discrete-variable optimization method. The modal approximation technique is coupled with a standard conjugate-gradient continuous optimization method. The agreement between the two sets of results is good, validating both the approximate analysis and optimality of the results.
STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.
Dwork, Cynthia; Feldman, Vitaly; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Roth, Aaron
2015-08-01
Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses. PMID:26250683
Data and statistical methods for analysis of trends and patterns
Atwood, C.L.; Gentillon, C.D.; Wilson, G.E.
1992-11-01
This report summarizes topics considered at a working meeting on data and statistical methods for analysis of trends and patterns in US commercial nuclear power plants. This meeting was sponsored by the Office of Analysis and Evaluation of Operational Data (AEOD) of the Nuclear Regulatory Commission (NRC). Three data sets are briefly described: Nuclear Plant Reliability Data System (NPRDS), Licensee Event Report (LER) data, and Performance Indicator data. Two types of study are emphasized: screening studies, to see if any trends or patterns appear to be present; and detailed studies, which are more concerned with checking the analysis assumptions, modeling any patterns that are present, and searching for causes. A prescription is given for a screening study, and ideas are suggested for a detailed study, when the data take of any of three forms: counts of events per time, counts of events per demand, and non-event data.
Managing Performance Analysis with Dynamic Statistical Projection Pursuit
Vetter, J.S.; Reed, D.A.
2000-05-22
Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focusing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.
ERIC Educational Resources Information Center
Metz, Anneke M.
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…
Gis-Based Spatial Statistical Analysis of College Graduates Employment
NASA Astrophysics Data System (ADS)
Tang, R.
2012-07-01
It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.
Statistical energy analysis of a geared rotor system
NASA Technical Reports Server (NTRS)
Lim, Teik C.; Singh, Rajendra
1990-01-01
The vibroacoustic response of a generic geared rotor system is analyzed on an order of magnitude basis utilizing an approximate statistical energy analysis method. This model includes a theoretical coupling loss factor for a generic bearing component, which properly accounts for the vibration transmission through rolling element bearing. A simplified model of a NASA test stand that assumes vibratory energy flow from the gear mesh source to the casing through shafts and bearings is given as an example. Effects of dissipation loss factor and gearbox radiation efficiency models are studied by comparing predictions with NASA test results.
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.
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.
Data collection, computation and statistical analysis in psychophysiological experiments.
Buzzi, R; Wespi, J; Zwimpfer, J
1982-01-01
The system was designed to allow simultaneous monitoring of eight bioelectrical signals together with the necessary event markers. The data inputs are pulse code modulated, recorded on magnetic tape, and then read into a minicomputer. The computer permits the determination of parameters for the following signals: electrocardiogram (ECG), respiration (RESP), skin conductance changes (SCC), electromyogram (EMG), plethysmogram (PLET), pulse transmission time (PTT), and electroencephalogram (EEG). These parameters are determined for time blocks of selectable duration and read into a mainframe computer for further statistical analysis. PMID:7183101
Skylab 2 ground winds data reduction and statistical analysis
NASA Technical Reports Server (NTRS)
1974-01-01
A ground winds test was conducted on the Skylab 2 spacecraft in a subsonic wind tunnel and the results were tape recorded for analysis. The data reduction system used to analyze the tapes for full scale, first and second mode bending moments, or acceleration plots versus dynamic pressure or wind velocity is explained. Portions of the Skylab 2 tape data were analyzed statistically in the form of power spectral densities, autocorrelations, and cross correlations to introduce a concept of using system response decay as a measure of linear system damping.
Multi-scale statistical analysis of coronal solar activity
NASA Astrophysics Data System (ADS)
Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.
2016-07-01
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.
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).
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 analysis of the 70 meter antenna surface distortions
NASA Technical Reports Server (NTRS)
Kiedron, K.; Chian, C. T.; Chuang, K. L.
1987-01-01
Statistical analysis of surface distortions of the 70 meter NASA/JPL antenna, located at Goldstone, was performed. The purpose of this analysis is to verify whether deviations due to gravity loading can be treated as quasi-random variables with normal distribution. Histograms of the RF pathlength error distribution for several antenna elevation positions were generated. The results indicate that the deviations from the ideal antenna surface are not normally distributed. The observed density distribution for all antenna elevation angles is taller and narrower than the normal density, which results in large positive values of kurtosis and a significant amount of skewness. The skewness of the distribution changes from positive to negative as the antenna elevation changes from zenith to horizon.
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.
Processes and subdivisions in diogenites, a multivariate statistical analysis
NASA Technical Reports Server (NTRS)
Harriott, T. A.; Hewins, R. H.
1984-01-01
Multivariate statistical techniques used on diogenite orthopyroxene analyses show the relationships that occur within diogenites and the two orthopyroxenite components (class I and II) in the polymict diogenite Garland. Cluster analysis shows that only Peckelsheim is similar to Garland class I (Fe-rich) and the other diogenites resemble Garland class II. The unique diogenite Y 75032 may be related to type I by fractionation. Factor analysis confirms the subdivision and shows that Fe does not correlate with the weakly incompatible elements across the entire pyroxene composition range, indicating that igneous fractionation is not the process controlling total diogenite composition variation. The occurrence of two groups of diogenites is interpreted as the result of sampling or mixing of two main sequences of orthopyroxene cumulates with slightly different compositions.
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.
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.
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.
Statistical analysis and correlation discovery of tumor respiratory motion.
Wu, Huanmei; Sharp, Gregory C; Zhao, Qingya; Shirato, Hiroki; Jiang, Steve B
2007-08-21
Tumors, especially in the thorax and abdomen, are subject to respiratory motion, and understanding the structure of respiratory motion is a key component to the management and control of disease in these sites. We have applied statistical analysis and correlation discovery methods to analyze and mine tumor respiratory motion based on a finite state model of tumor motion. Aggregates (such as minimum, maximum, average and mean), histograms, percentages, linear regression and multi-round statistical analysis have been explored. The results have been represented in various formats, including tables, graphs and text description. Different graphs, for example scatter plots, clustered column figures, 100% stacked column figures and box-whisker plots, have been applied to highlight different aspects of the results. The internal tumor motion from 42 lung tumors, 30 of which have motion larger than 5 mm, has been analyzed. Results for both inter-patient and intra-patient motion characteristics, such as duration and travel distance patterns, are reported. New knowledge of patient-specific tumor motion characteristics have been discovered, such as expected correlations between properties. The discovered tumor motion characteristics will be utilized in different aspects of image-guided radiation treatment, including treatment planning, online tumor motion prediction and real-time radiation dose delivery. PMID:17671334
Statistical analysis and correlation discovery of tumor respiratory motion
NASA Astrophysics Data System (ADS)
Wu, Huanmei; Sharp, Gregory C.; Zhao, Qingya; Shirato, Hiroki; Jiang, Steve B.
2007-08-01
Tumors, especially in the thorax and abdomen, are subject to respiratory motion, and understanding the structure of respiratory motion is a key component to the management and control of disease in these sites. We have applied statistical analysis and correlation discovery methods to analyze and mine tumor respiratory motion based on a finite state model of tumor motion. Aggregates (such as minimum, maximum, average and mean), histograms, percentages, linear regression and multi-round statistical analysis have been explored. The results have been represented in various formats, including tables, graphs and text description. Different graphs, for example scatter plots, clustered column figures, 100% stacked column figures and box-whisker plots, have been applied to highlight different aspects of the results. The internal tumor motion from 42 lung tumors, 30 of which have motion larger than 5 mm, has been analyzed. Results for both inter-patient and intra-patient motion characteristics, such as duration and travel distance patterns, are reported. New knowledge of patient-specific tumor motion characteristics have been discovered, such as expected correlations between properties. The discovered tumor motion characteristics will be utilized in different aspects of image-guided radiation treatment, including treatment planning, online tumor motion prediction and real-time radiation dose delivery.
Analysis of ageing of amorphous thermoplastic polymers by PVT analysis
NASA Astrophysics Data System (ADS)
Greco, Antonio; Maffezzoli, Alfonso; Gennaro, Riccardo; Rizzo, Michele
2012-07-01
The aim of this work is the analysis of ageing phenomenon occurring in amorphous thermoplastic polymers below their glass transition temperature by pressure-volume-temperature (PVT) analysis. The ageing behavior of different polymers as a function of the heating and cooling rates has been widespread studied. Also, different works in literature are aimed to study the effect of the applied pressure on the glass transition behavior. Another relevant aspect related to the glass transition behavior is related to the ageing effects, which can also be influenced by the applied pressure. This is a very relevant issue, since most of the polymers, during ageing, are subjected to mechanical loading. PVT analysis was used to study the ageing of amorphous PET copolymer (PETg) at different pressure levels. Specific volume-temperature curves measured during the cooling and the heating steps were used for calculating the relaxed specific volume, showing that ageing effects increase with increasing applied pressure. The evolution of the fictive temperature as a function of time was calculated from experimental data.
Neutral dynamics with environmental noise: Age-size statistics and species lifetimes
NASA Astrophysics Data System (ADS)
Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.
2015-08-01
Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.
Neutral dynamics with environmental noise: Age-size statistics and species lifetimes.
Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M
2015-08-01
Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O√N)] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems--age-size relationships and species extinction time--in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics. PMID:26382447
EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon
2015-08-01
Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). PMID:25913743
Statistical Models and Methods for Network Meta-Analysis.
Madden, L V; Piepho, H-P; Paul, P A
2016-08-01
Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS. PMID:27111798
A statistical analysis of the internal organ weights of normal Japanese people
Ogiu, Nobuko; Nakamura, Yuji; Ogiu, Toshiaki
1997-03-01
Correlation of weights of various organs with age, body weight, and/or body height was statistically analyzed using data on the Japanese physique collected by the Medico-Legal Society from Universities and Research Institutes in almost all areas of Japan. After exclusion of unsuitable individual data for statistical analysis, findings for 4,667 Japanese, aged 0-95 y, including 3,023 males and 1,644 females were used in the present study. Analyses of age-dependent changes in weights of the brain, heart, lung, kidney, spleen, pancreas, thymus, thyroid gland and adrenal gland and also of correlations between organ weights and body height, weight, or surface area were carried out. It was concluded that organ weights in the growing generation (under 19 y) generally increased with a coefficient expressed as (body height X body weight{sup 0.5}). Because clear age-dependent changes were not observed in adults over 20 y, they were classified into 4 physical types, thin, standard, plump and obese, and the relations of organ weights with these physical types were assessed. Some organs were relatively heavier in fat groups and light in thin individuals, or vice versa. 36 refs., 5 figs., 11 tabs.
Transcriptome analysis of aging mouse meibomian glands
Parfitt, Geraint J.; Brown, Donald J.
2016-01-01
Purpose Dry eye disease is a common condition associated with age-related meibomian gland dysfunction (ARMGD). We have previously shown that ARMGD occurs in old mice, similar to that observed in human patients with MGD. To begin to understand the mechanism underlying ARMGD, we generated transcriptome profiles of eyelids excised from young and old mice of both sexes. Methods Male and female C57BL/6 mice were euthanized at ages of 3 months or 2 years and their lower eyelids removed, the conjunctival epithelium scrapped off, and the tarsal plate, containing the meibomian glands, dissected from the overlying muscle and lid epidermis. RNA was isolated, enriched, and transcribed into cDNA and processed to generate four non-stranded libraries with distinct bar codes on each adaptor. The libraries were then sequenced and mapped to the mm10 reference genome, and expression results were gathered as reads per length of transcript in kilobases per million mapped reads (RPKM) values. Differential gene expression analyses were performed using CyberT. Results Approximately 55 million reads were generated from each library. Expression data indicated that about 15,000 genes were expressed in these tissues. Of the genes that showed more than twofold significant differences in either young or old tissue, 698 were identified as differentially expressed. According to the Gene Ontology (GO) analysis, the cellular, developmental, and metabolic processes were found to be highly represented with Wnt function noted to be altered in the aging mouse. Conclusions The RNA sequencing data identified several signaling pathways, including fibroblast growth factor (FGF) and Wnt that were altered in the meibomian glands of aging mice. PMID:27279727
Statistical analysis of magnetotail fast flows and related magnetic disturbances
NASA Astrophysics Data System (ADS)
Frühauff, Dennis; Glassmeier, Karl-Heinz
2016-04-01
This study presents an investigation on the occurrence of fast flows in the magnetotail using the complete available data set of the THEMIS spacecraft for the years 2007 to 2015. The fast flow events (times of enhanced ion velocity) are detected through the use of a velocity criterion, therefore making the resulting database as large as almost 16 000 events. First, basic statistical findings concerning velocity distributions, occurrence rates, group structures are presented. Second, Superposed Epoch Analysis is utilized to account for average profiles of selected plasma quantities. The data reveal representative time series in near and far tail of the Earth with typical timescales of the order of 1-2 min, corresponding to scale sizes of 3 RE. Last, related magnetic field disturbances are analyzed. It is found that the minimum variance direction is essentially confined to a plane almost perpendicular to the main flow direction while, at the same time, the maximum variance direction is aligned with flow and background field directions. The presentation of the database and first statistical findings will prove useful both as input for magneto-hydrodynamical simulations and theoretical considerations of fast flows.
Statistical methods for the analysis of climate extremes
NASA Astrophysics Data System (ADS)
Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent
2005-08-01
Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).
ADS-Demo Fuel Rod Performance: Multivariate Statistical Analysis
Calabrese, R.; Vettraino, F.; Luzzi, L.
2004-07-01
A forward step in the development of Accelerator Driven System (ADS) for the Pu, MA and LLFP transmutation, is the realisation of a 80 MWt ADS-demo (XADS) whose basic objective is the system feasibility demonstration. The XADS is forecasted to adopt the UO{sub 2}-PuO{sub 2} mixed-oxides fuel already experimented in the sodium cooled fast reactors such as the french SPX-1. The present multivariate statistical analysis performed by using the Transuranus Code, was carried out for the Normal Operation at the so-called Enhanced Nominal Conditions (120% nominal reactor power), aimed at verifying that the fuel system complies with the stated design limits, i.e. centerline fuel temperature, cladding temperature and damage, during all the in-reactor lifetime. A statistical input set similar to SPX and PEC fuel case, was adopted. One most relevant assumption in the present calculations was a 30% AISI-316 cladding thickness corrosion at EOL. Relative influence of main fuel rod parameters on fuel centerline temperature was also evaluated. (authors)
Confirmatory Factor Analysis of the Statistical Anxiety Rating Scale With Online Graduate Students.
DeVaney, Thomas A
2016-04-01
The Statistical Anxiety Rating Scale was examined using data from a convenience sample of 450 female and 65 male students enrolled in online, graduate-level introductory statistics courses. The mean age of the students was 33.1 (SD = 8.2), and 58.3% had completed six or fewer online courses. The majority of students were enrolled in education or counseling degree programs. Confirmatory factor analysis using unweighted least squares estimation was used to test three proposed models, and alpha coefficients were used to examine the internal consistency. The confirmatory factor analysis results supported the six-factor structure and indicated that proper models should include correlations among the six factors or two second-order factors (anxiety and attitude). Internal consistency estimates ranged from .82 to .95 and were consistent with values reported by previous researchers. The findings suggest that, when measuring statistics anxiety of online students using Statistical Anxiety Rating Scale, researchers and instructors can use scores from the individual subscales or generate two composite scores, anxiety and attitude, instead of a total score. PMID:27154380
Statistical Analysis of Risk Factors in the Prebreathe Reduction Protocol
NASA Technical Reports Server (NTRS)
Gerth, Wayne A.; Gernhardt, Michael L.; Conkin, Johnny; Homick, Jerry L. (Technical Monitor)
2000-01-01
The 165 exposures from four 2-hour protocols were analyzed for correlations or trends between decompression sickness (DCS) or venous gas emboli (VGE), and variables that affect risk in the subject and astronaut populations. The assumption in this global survey is that the distributions of gender, age, body mass index, etc., are equally represented in all four tested procedures. We used Student t-test for comparisons between means and chi-square test between comparisons of proportions with p<0.05 defining a significant level. The type and distribution of the 19 cases of DCS were similar to historical cases. There was no correlation of age, gender, body mass index or fitness level with greater incidence of DCS or VGE. However increased age was associated with more Grade IV VGE in males. The duration and quantity of exercise during prebreathe is inversely related to risk of DCS and VGE. The latency time for VGE was longer (103 min +/- 56 SD, n = 15) when the ergometry was done approximately 15 min into the prebreathe than when done at the start of the prebreathe (53 min +/- 31, n = 13). The order of the ergometry did not influence the overall DCS and VGE incidence. We identified variables other than those of the prebreathe procedures that influence the DCS and VGE outcome. The analysis suggests that males over 40 years have a high incidence of Grade IV VGE.
Statistical analysis of target acquisition sensor modeling experiments
NASA Astrophysics Data System (ADS)
Deaver, Dawne M.; Moyer, Steve
2015-05-01
The U.S. Army RDECOM CERDEC NVESD Modeling and Simulation Division is charged with the development and advancement of military target acquisition models to estimate expected soldier performance when using all types of imaging sensors. Two elements of sensor modeling are (1) laboratory-based psychophysical experiments used to measure task performance and calibrate the various models and (2) field-based experiments used to verify the model estimates for specific sensors. In both types of experiments, it is common practice to control or measure environmental, sensor, and target physical parameters in order to minimize uncertainty of the physics based modeling. Predicting the minimum number of test subjects required to calibrate or validate the model should be, but is not always, done during test planning. The objective of this analysis is to develop guidelines for test planners which recommend the number and types of test samples required to yield a statistically significant result.