Item Analysis Appropriate for Domain-Referenced Classroom Testing. (Project Technical Report Number 1).

ERIC Educational Resources Information Center

Nitko, Anthony J.; Hsu, Tse-chi

Item analysis procedures appropriate for domain-referenced classroom testing are described. A conceptual framework within which item statistics can be considered and promising statistics in light of this framework are presented. The sampling fluctuations of the more promising item statistics for sample sizes comparable to the typical classroom…

Crash analysis, statistics & information notebook 1996-2003

DOT National Transportation Integrated Search

2004-11-01

The Department of Motor Vehicle Safety is proud to present the Crash Analysis, Statistics & : Information (CASI) Notebook 1996-2003. DMVS developed the CASI Notebooks to provide : straightforward, easy to understand crash information. Each page or ta...

Statistical analysis of the count and profitability of air conditioners.

PubMed

Rady, El Houssainy A; Mohamed, Salah M; Abd Elmegaly, Alaa A

2018-08-01

This article presents the statistical analysis of the number and profitability of air conditioners in an Egyptian company. Checking the same distribution for each categorical variable has been made using Kruskal-Wallis test.

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.

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

Glascock, M. D.; Neff, H.; Vaughn, K. J.

2004-06-01

The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

Some issues in the statistical analysis of vehicle emissions

DOT National Transportation Integrated Search

2000-09-01

Some of the issues complicating the statistical analysis of vehicle emissions and the effectiveness of emissions control programs are presented in this article. Issues discussed include: the variability of inter- and intra-vehicle emissions; the skew...

Evaluation of The Operational Benefits Versus Costs of An Automated Cargo Mover

DTIC Science & Technology

2016-12-01

logistics footprint and life-cycle cost are presented as part of this report. Analysis of modeling and simulation results identified statistically...life-cycle cost are presented as part of this report. Analysis of modeling and simulation results identified statistically significant differences...Error of Estimation. Source: Eskew and Lawler (1994). ...........................75 Figure 24. Load Results (100 Runs per Scenario

A First Assignment to Create Student Buy-In in an Introductory Business Statistics Course

ERIC Educational Resources Information Center

Newfeld, Daria

2016-01-01

This paper presents a sample assignment to be administered after the first two weeks of an introductory business focused statistics course in order to promote student buy-in. This assignment integrates graphical displays of data, descriptive statistics and cross-tabulation analysis through the lens of a marketing analysis study. A marketing sample…

Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

NASA Technical Reports Server (NTRS)

He, Yuning; Davies, Misty Dawn

2014-01-01

The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

The Higher Education System in Israel: Statistical Abstract and Analysis.

ERIC Educational Resources Information Center

Herskovic, Shlomo

This edition of a statistical abstract published every few years on the higher education system in Israel presents the most recent data available through 1990-91. The data were gathered through the cooperation of the Central Bureau of Statistics and institutions of higher education. Chapter 1 presents a summary of principal findings covering the…

An Analysis of Effects of Variable Factors on Weapon Performance

DTIC Science & Technology

1993-03-01

ALTERNATIVE ANALYSIS A. CATEGORICAL DATA ANALYSIS Statistical methodology for categorical data analysis traces its roots to the work of Francis Galton in the...choice of statistical tests . This thesis examines an analysis performed by Surface Warfare Development Group (SWDG). The SWDG analysis is shown to be...incorrect due to the misapplication of testing methods. A corrected analysis is presented and recommendations suggested for changes to the testing

Parallel auto-correlative statistics with VTK.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pebay, Philippe Pierre; Bennett, Janine Camille

2013-08-01

This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

Analysis Code - Data Analysis in 'Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications' (LMSMIPNFA) v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, John R

R code that performs the analysis of a data set presented in the paper ‘Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications’ by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.

Systems and methods for detection of blowout precursors in combustors

DOEpatents

Lieuwen, Tim C.; Nair, Suraj

2006-08-15

The present invention comprises systems and methods for detecting flame blowout precursors in combustors. The blowout precursor detection system comprises a combustor, a pressure measuring device, and blowout precursor detection unit. A combustion controller may also be used to control combustor parameters. The methods of the present invention comprise receiving pressure data measured by an acoustic pressure measuring device, performing one or a combination of spectral analysis, statistical analysis, and wavelet analysis on received pressure data, and determining the existence of a blowout precursor based on such analyses. The spectral analysis, statistical analysis, and wavelet analysis further comprise their respective sub-methods to determine the existence of blowout precursors.

Statistical analysis of sparse infection data and its implications for retroviral treatment trials in primates.

PubMed Central

Spouge, J L

1992-01-01

Reports on retroviral primate trials rarely publish any statistical analysis. Present statistical methodology lacks appropriate tests for these trials and effectively discourages quantitative assessment. This paper describes the theory behind VACMAN, a user-friendly computer program that calculates statistics for in vitro and in vivo infectivity data. VACMAN's analysis applies to many retroviral trials using i.v. challenges and is valid whenever the viral dose-response curve has a particular shape. Statistics from actual i.v. retroviral trials illustrate some unappreciated principles of effective animal use: dilutions other than 1:10 can improve titration accuracy; infecting titration animals at the lowest doses possible can lower challenge doses; and finally, challenging test animals in small trials with more virus than controls safeguards against false successes, "reuses" animals, and strengthens experimental conclusions. The theory presented also explains the important concept of viral saturation, a phenomenon that may cause in vitro and in vivo titrations to agree for some retroviral strains and disagree for others. PMID:1323844

Proceedings of the first ERDA statistical symposium, Los Alamos, NM, November 3--5, 1975. [Sixteen papers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicholson, W L; Harris, J L

1976-03-01

The First ERDA Statistical Symposium was organized to provide a means for communication among ERDA statisticians, and the sixteen papers presented at the meeting are given. Topics include techniques of numerical analysis used for accelerators, nuclear reactors, skewness and kurtosis statistics, radiochemical spectral analysis, quality control, and other statistics problems. Nine of the papers were previously announced in Nuclear Science Abstracts (NSA), while the remaining seven were abstracted for ERDA Energy Research Abstracts (ERA) and INIS Atomindex. (PMA)

Statistical methodology for the analysis of dye-switch microarray experiments

PubMed Central

Mary-Huard, Tristan; Aubert, Julie; Mansouri-Attia, Nadera; Sandra, Olivier; Daudin, Jean-Jacques

2008-01-01

Background In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis. Results We present two original statistical procedures for the statistical analysis of individually balanced designs. These procedures are compared with the usual ML and REML mixed model procedures proposed in most statistical toolboxes, on both simulated and real data. Conclusion The UP procedure we propose as an alternative to usual mixed model procedures is more efficient and significantly faster to compute. This result provides some useful guidelines for the analysis of complex designs. PMID:18271965

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kogalovskii, M.R.

This paper presents a review of problems related to statistical database systems, which are wide-spread in various fields of activity. Statistical databases (SDB) are referred to as databases that consist of data and are used for statistical analysis. Topics under consideration are: SDB peculiarities, properties of data models adequate for SDB requirements, metadata functions, null-value problems, SDB compromise protection problems, stored data compression techniques, and statistical data representation means. Also examined is whether the present Database Management Systems (DBMS) satisfy the SDB requirements. Some actual research directions in SDB systems are considered.

Suggestions for presenting the results of data analyses

USGS Publications Warehouse

Anderson, David R.; Link, William A.; Johnson, Douglas H.; Burnham, Kenneth P.

2001-01-01

We give suggestions for the presentation of research results from frequentist, information-theoretic, and Bayesian analysis paradigms, followed by several general suggestions. The information-theoretic and Bayesian methods offer alternative approaches to data analysis and inference compared to traditionally used methods. Guidance is lacking on the presentation of results under these alternative procedures and on nontesting aspects of classical frequentists methods of statistical analysis. Null hypothesis testing has come under intense criticism. We recommend less reporting of the results of statistical tests of null hypotheses in cases where the null is surely false anyway, or where the null hypothesis is of little interest to science or management.

Considerations for the design, analysis and presentation of in vivo studies.

PubMed

Ranstam, J; Cook, J A

2017-03-01

To describe, explain and give practical suggestions regarding important principles and key methodological challenges in the study design, statistical analysis, and reporting of results from in vivo studies. Pre-specifying endpoints and analysis, recognizing the common underlying assumption of statistically independent observations, performing sample size calculations, and addressing multiplicity issues are important parts of an in vivo study. A clear reporting of results and informative graphical presentations of data are other important parts. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Noise limitations in optical linear algebra processors.

PubMed

Batsell, S G; Jong, T L; Walkup, J F; Krile, T F

1990-05-10

A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.

Source apportionment of groundwater pollution around landfill site in Nagpur, India.

PubMed

Pujari, Paras R; Deshpande, Vijaya

2005-12-01

The present work attempts statistical analysis of groundwater quality near a Landfill site in Nagpur, India. The objective of the present work is to figure out the impact of different factors on the quality of groundwater in the study area. Statistical analysis of the data has been attempted by applying Factor Analysis concept. The analysis brings out the effect of five different factors governing the groundwater quality in the study area. Based on the contribution of the different parameters present in the extracted factors, the latter are linked to the geological setting, the leaching from the host rock, leachate of heavy metals from the landfill as well as the bacterial contamination from landfill site and other anthropogenic activities. The analysis brings out the vulnerability of the unconfined aquifer to contamination.

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.…

Analysis and interpretation of cost data in randomised controlled trials: review of published studies

PubMed Central

Barber, Julie A; Thompson, Simon G

1998-01-01

Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study. Design Survey of published randomised trials including an economic evaluation with cost values suitable for statistical analysis; 45 such trials published in 1995 were identified from Medline. Main outcome measures The use of statistical methods for cost data was assessed in terms of the descriptive statistics reported, use of statistical inference, and whether the reported conclusions were justified. Results Although all 45 trials reviewed apparently had cost data for each patient, only 9 (20%) reported adequate measures of variability for these data and only 25 (56%) gave results of statistical tests or a measure of precision for the comparison of costs between the randomised groups. Only 16 (36%) of the articles gave conclusions which were justified on the basis of results presented in the paper. No paper reported sample size calculations for costs. Conclusions The analysis and interpretation of cost data from published trials reveal a lack of statistical awareness. Strong and potentially misleading conclusions about the relative costs of alternative therapies have often been reported in the absence of supporting statistical evidence. Improvements in the analysis and reporting of health economic assessments are urgently required. Health economic guidelines need to be revised to incorporate more detailed statistical advice. Key messagesHealth economic evaluations required for important healthcare policy decisions are often carried out in randomised controlled trialsA review of such published economic evaluations assessed whether statistical methods for cost outcomes have been appropriately used and interpretedFew publications presented adequate descriptive information for costs or performed appropriate statistical analysesIn at least two thirds of the papers, the main conclusions regarding costs were not justifiedThe analysis and reporting of health economic assessments within randomised controlled trials urgently need improving PMID:9794854

Doppler and speckle methods for diagnostics in dentistry

NASA Astrophysics Data System (ADS)

Ulyanov, Sergey S.; Lepilin, Alexander V.; Lebedeva, Nina G.; Sedykh, Alexey V.; Kharish, Natalia A.; Osipova, Yulia; Karpovich, Alexander

2002-02-01

The results of statistical analysis of Doppler spectra of scattered intensity, obtained from tissues of oral cavity membrane of healthy volunteers, are presented. The dependence of the spectral moments of Doppler signal on cutoff frequency is investigated. Some results of statistical analysis of Doppler spectra, obtained from tooth pulp of patients, are presented. New approach for monitoring of blood microcirculation in orthodontics is suggested. Influence of own noise of measuring system on formation of speckle-interferometric signal is studied.

An evaluation of the quality of statistical design and analysis of published medical research: results from a systematic survey of general orthopaedic journals.

PubMed

Parsons, Nick R; Price, Charlotte L; Hiskens, Richard; Achten, Juul; Costa, Matthew L

2012-04-25

The application of statistics in reported research in trauma and orthopaedic surgery has become ever more important and complex. Despite the extensive use of statistical analysis, it is still a subject which is often not conceptually well understood, resulting in clear methodological flaws and inadequate reporting in many papers. A detailed statistical survey sampled 100 representative orthopaedic papers using a validated questionnaire that assessed the quality of the trial design and statistical analysis methods. The survey found evidence of failings in study design, statistical methodology and presentation of the results. Overall, in 17% (95% confidence interval; 10-26%) of the studies investigated the conclusions were not clearly justified by the results, in 39% (30-49%) of studies a different analysis should have been undertaken and in 17% (10-26%) a different analysis could have made a difference to the overall conclusions. It is only by an improved dialogue between statistician, clinician, reviewer and journal editor that the failings in design methodology and analysis highlighted by this survey can be addressed.

Probability and Statistics: A Prelude.

ERIC Educational Resources Information Center

Goodman, A. F.; Blischke, W. R.

Probability and statistics have become indispensable to scientific, technical, and management progress. They serve as essential dialects of mathematics, the classical language of science, and as instruments necessary for intelligent generation and analysis of information. A prelude to probability and statistics is presented by examination of the…

Social and economic sustainability of urban systems: comparative analysis of metropolitan statistical areas in Ohio, USA

EPA Science Inventory

This article presents a general and versatile methodology for assessing sustainability with Fisher Information as a function of dynamic changes in urban systems. Using robust statistical methods, six Metropolitan Statistical Areas (MSAs) in Ohio were evaluated to comparatively as...

Statistical evaluation of vibration analysis techniques

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Miller, Patrice S.

1987-01-01

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

Students' Appreciation of Expectation and Variation as a Foundation for Statistical Understanding

ERIC Educational Resources Information Center

Watson, Jane M.; Callingham, Rosemary A.; Kelly, Ben A.

2007-01-01

This study presents the results of a partial credit Rasch analysis of in-depth interview data exploring statistical understanding of 73 school students in 6 contextual settings. The use of Rasch analysis allowed the exploration of a single underlying variable across contexts, which included probability sampling, representation of temperature…

Anomalous heat transfer modes of nanofluids: a review based on statistical analysis

NASA Astrophysics Data System (ADS)

Sergis, Antonis; Hardalupas, Yannis

2011-05-01

This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.

Anomalous heat transfer modes of nanofluids: a review based on statistical analysis.

PubMed

Sergis, Antonis; Hardalupas, Yannis

2011-05-19

This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.

Anomalous heat transfer modes of nanofluids: a review based on statistical analysis

PubMed Central

2011-01-01

This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids. PMID:21711932

The Statistical Interpretation of Classical Thermodynamic Heating and Expansion Processes

ERIC Educational Resources Information Center

Cartier, Stephen F.

2011-01-01

A statistical model has been developed and applied to interpret thermodynamic processes typically presented from the macroscopic, classical perspective. Through this model, students learn and apply the concepts of statistical mechanics, quantum mechanics, and classical thermodynamics in the analysis of the (i) constant volume heating, (ii)…

Statistical analysis of arthroplasty data

PubMed Central

2011-01-01

It is envisaged that guidelines for statistical analysis and presentation of results will improve the quality and value of research. The Nordic Arthroplasty Register Association (NARA) has therefore developed guidelines for the statistical analysis of arthroplasty register data. The guidelines are divided into two parts, one with an introduction and a discussion of the background to the guidelines (Ranstam et al. 2011a, see pages x-y in this issue), and this one with a more technical statistical discussion on how specific problems can be handled. This second part contains (1) recommendations for the interpretation of methods used to calculate survival, (2) recommendations on howto deal with bilateral observations, and (3) a discussion of problems and pitfalls associated with analysis of factors that influence survival or comparisons between outcomes extracted from different hospitals. PMID:21619500

A Study of the NASS-CDS System for Injury/Fatality Rates of Occupants in Various Restraints and A Discussion of Alternative Presentation Methods

PubMed Central

Stucki, Sheldon Lee; Biss, David J.

2000-01-01

An analysis was performed using the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) database to compare the injury/fatality rates of variously restrained driver occupants as compared to unrestrained driver occupants in the total database of drivers/frontals, and also by Delta-V. A structured search of the NASS-CDS was done using the SAS® statistical analysis software to extract the data for this analysis and the SUDAAN software package was used to arrive at statistical significance indicators. In addition, this paper goes on to investigate different methods for presenting results of accident database searches including significance results; a risk versus Delta-V format for specific exposures; and, a percent cumulative injury versus Delta-V format to characterize injury trends. These alternative analysis presentation methods are then discussed by example using the present study results. PMID:11558105

Conditional statistics in a turbulent premixed flame derived from direct numerical simulation

NASA Technical Reports Server (NTRS)

Mantel, Thierry; Bilger, Robert W.

1994-01-01

The objective of this paper is to briefly introduce conditional moment closure (CMC) methods for premixed systems and to derive the transport equation for the conditional species mass fraction conditioned on the progress variable based on the enthalpy. Our statistical analysis will be based on the 3-D DNS database of Trouve and Poinsot available at the Center for Turbulence Research. The initial conditions and characteristics (turbulence, thermo-diffusive properties) as well as the numerical method utilized in the DNS of Trouve and Poinsot are presented, and some details concerning our statistical analysis are also given. From the analysis of DNS results, the effects of the position in the flame brush, of the Damkoehler and Lewis numbers on the conditional mean scalar dissipation, and conditional mean velocity are presented and discussed. Information concerning unconditional turbulent fluxes are also presented. The anomaly found in previous studies of counter-gradient diffusion for the turbulent flux of the progress variable is investigated.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

SMAR Sessions

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Robert

2011-01-01

This slide presentation is a series of educational presentations that are on the statistical function of analysis of variance (ANOVA). Analysis of Variance (ANOVA) examines variability between groups, relative to within groups, to determine whether there's evidence that the groups are not from the same population. One other presentation reviews hypothesis testing.

Comparative analysis of ferroelectric domain statistics via nonlinear diffraction in random nonlinear materials.

PubMed

Wang, B; Switowski, K; Cojocaru, C; Roppo, V; Sheng, Y; Scalora, M; Kisielewski, J; Pawlak, D; Vilaseca, R; Akhouayri, H; Krolikowski, W; Trull, J

2018-01-22

We present an indirect, non-destructive optical method for domain statistic characterization in disordered nonlinear crystals having homogeneous refractive index and spatially random distribution of ferroelectric domains. This method relies on the analysis of the wave-dependent spatial distribution of the second harmonic, in the plane perpendicular to the optical axis in combination with numerical simulations. We apply this technique to the characterization of two different media, Calcium Barium Niobate and Strontium Barium Niobate, with drastically different statistical distributions of ferroelectric domains.

Graphical tools for network meta-analysis in STATA.

PubMed

Chaimani, Anna; Higgins, Julian P T; Mavridis, Dimitris; Spyridonos, Panagiota; Salanti, Georgia

2013-01-01

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

Graphical Tools for Network Meta-Analysis in STATA

PubMed Central

Chaimani, Anna; Higgins, Julian P. T.; Mavridis, Dimitris; Spyridonos, Panagiota; Salanti, Georgia

2013-01-01

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results. PMID:24098547

Regression Analysis and the Sociological Imagination

ERIC Educational Resources Information Center

De Maio, Fernando

2014-01-01

Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

Black Females in High School: A Statistical Educational Profile

ERIC Educational Resources Information Center

Muhammad, Crystal Gafford; Dixson, Adrienne D.

2008-01-01

In life as in literature, both the mainstream public and the Black community writ large, overlook the Black female experiences, both adolescent and adult. In order to contribute to the knowledge base regarding this population, we present through our study a statistical portrait of Black females in high school. To do so, we present an analysis of…

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

Interpolative modeling of GaAs FET S-parameter data bases for use in Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Campbell, L.; Purviance, J.

1992-01-01

A statistical interpolation technique is presented for modeling GaAs FET S-parameter measurements for use in the statistical analysis and design of circuits. This is accomplished by interpolating among the measurements in a GaAs FET S-parameter data base in a statistically valid manner.

A Descriptive Study of Individual and Cross-Cultural Differences in Statistics Anxiety

ERIC Educational Resources Information Center

Baloglu, Mustafa; Deniz, M. Engin; Kesici, Sahin

2011-01-01

The present study investigated individual and cross-cultural differences in statistics anxiety among 223 Turkish and 237 American college students. A 2 x 2 between-subjects factorial multivariate analysis of covariance (MANCOVA) was performed on the six dependent variables which are the six subscales of the Statistical Anxiety Rating Scale.…

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PubMed

Golder, W

1999-09-01

To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

Primer of statistics in dental research: part I.

PubMed

Shintani, Ayumi

2014-01-01

Statistics play essential roles in evidence-based dentistry (EBD) practice and research. It ranges widely from formulating scientific questions, designing studies, collecting and analyzing data to interpreting, reporting, and presenting study findings. Mastering statistical concepts appears to be an unreachable goal among many dental researchers in part due to statistical authorities' limitations of explaining statistical principles to health researchers without elaborating complex mathematical concepts. This series of 2 articles aim to introduce dental researchers to 9 essential topics in statistics to conduct EBD with intuitive examples. The part I of the series includes the first 5 topics (1) statistical graph, (2) how to deal with outliers, (3) p-value and confidence interval, (4) testing equivalence, and (5) multiplicity adjustment. Part II will follow to cover the remaining topics including (6) selecting the proper statistical tests, (7) repeated measures analysis, (8) epidemiological consideration for causal association, and (9) analysis of agreement. Copyright © 2014. Published by Elsevier Ltd.

A Primer on Bayesian Analysis for Experimental Psychopathologists

PubMed Central

Krypotos, Angelos-Miltiadis; Blanken, Tessa F.; Arnaudova, Inna; Matzke, Dora; Beckers, Tom

2016-01-01

The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by the adoption of Bayesian statistics than by the continued use of null-hypothesis significance testing (NHST). In the first part of the article we list the main disadvantages of NHST and explain why those disadvantages limit the conclusions that can be drawn from EPP research. Next, we highlight the advantages of Bayesian statistics. To illustrate, we then pit NHST and Bayesian analysis against each other using an experimental data set from our lab. Finally, we discuss some challenges when adopting Bayesian statistics. We hope that the present article will encourage experimental psychopathologists to embrace Bayesian statistics, which could strengthen the conclusions drawn from EPP research. PMID:28748068

Characterization and classification of oral tissues using excitation and emission matrix: a statistical modeling approach

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Gnanatheepaminstein, Einstein; Prakasarao, Aruna; Dornadula, Koteeswaran; Singaravelu, Ganesan

2017-02-01

Cancer is one of the most common human threats around the world and diagnosis based on optical spectroscopy especially fluorescence technique has been established as the standard approach among scientist to explore the biochemical and morphological changes in tissues. In this regard, the present work aims to extract spectral signatures of the various fluorophores present in oral tissues using parallel factor analysis (PARAFAC). Subsequently, the statistical analysis also to be performed to show its diagnostic potential in distinguishing malignant, premalignant from normal oral tissues. Hence, the present study may lead to the possible and/or alternative tool for oral cancer diagnosis.

Clustered Stomates in "Begonia": An Exercise in Data Collection & Statistical Analysis of Biological Space

ERIC Educational Resources Information Center

Lau, Joann M.; Korn, Robert W.

2007-01-01

In this article, the authors present a laboratory exercise in data collection and statistical analysis in biological space using clustered stomates on leaves of "Begonia" plants. The exercise can be done in middle school classes by students making their own slides and seeing imprints of cells, or at the high school level through collecting data of…

Analysis of half diallel mating designs I: a practical analysis procedure for ANOVA approximation.

Treesearch

G.R. Johnson; J.N. King

1998-01-01

Procedures to analyze half-diallel mating designs using the SAS statistical package are presented. The procedure requires two runs of PROC and VARCOMP and results in estimates of additive and non-additive genetic variation. The procedures described can be modified to work on most statistical software packages which can compute variance component estimates. The...

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications.

PubMed

Spriestersbach, Albert; Röhrig, Bernd; du Prel, Jean-Baptist; Gerhold-Ay, Aslihan; Blettner, Maria

2009-09-01

Descriptive statistics are an essential part of biometric analysis and a prerequisite for the understanding of further statistical evaluations, including the drawing of inferences. When data are well presented, it is usually obvious whether the author has collected and evaluated them correctly and in keeping with accepted practice in the field. Statistical variables in medicine may be of either the metric (continuous, quantitative) or categorical (nominal, ordinal) type. Easily understandable examples are given. Basic techniques for the statistical description of collected data are presented and illustrated with examples. The goal of a scientific study must always be clearly defined. The definition of the target value or clinical endpoint determines the level of measurement of the variables in question. Nearly all variables, whatever their level of measurement, can be usefully presented graphically and numerically. The level of measurement determines what types of diagrams and statistical values are appropriate. There are also different ways of presenting combinations of two independent variables graphically and numerically. The description of collected data is indispensable. If the data are of good quality, valid and important conclusions can already be drawn when they are properly described. Furthermore, data description provides a basis for inferential statistics.

Statistical quality control through overall vibration analysis

NASA Astrophysics Data System (ADS)

Carnero, M. ^a. Carmen; González-Palma, Rafael; Almorza, David; Mayorga, Pedro; López-Escobar, Carlos

2010-05-01

The present study introduces the concept of statistical quality control in automotive wheel bearings manufacturing processes. Defects on products under analysis can have a direct influence on passengers' safety and comfort. At present, the use of vibration analysis on machine tools for quality control purposes is not very extensive in manufacturing facilities. Noise and vibration are common quality problems in bearings. These failure modes likely occur under certain operating conditions and do not require high vibration amplitudes but relate to certain vibration frequencies. The vibration frequencies are affected by the type of surface problems (chattering) of ball races that are generated through grinding processes. The purpose of this paper is to identify grinding process variables that affect the quality of bearings by using statistical principles in the field of machine tools. In addition, an evaluation of the quality results of the finished parts under different combinations of process variables is assessed. This paper intends to establish the foundations to predict the quality of the products through the analysis of self-induced vibrations during the contact between the grinding wheel and the parts. To achieve this goal, the overall self-induced vibration readings under different combinations of process variables are analysed using statistical tools. The analysis of data and design of experiments follows a classical approach, considering all potential interactions between variables. The analysis of data is conducted through analysis of variance (ANOVA) for data sets that meet normality and homoscedasticity criteria. This paper utilizes different statistical tools to support the conclusions such as chi squared, Shapiro-Wilks, symmetry, Kurtosis, Cochran, Hartlett, and Hartley and Krushal-Wallis. The analysis presented is the starting point to extend the use of predictive techniques (vibration analysis) for quality control. This paper demonstrates the existence of predictive variables (high-frequency vibration displacements) that are sensible to the processes setup and the quality of the products obtained. Based on the result of this overall vibration analysis, a second paper will analyse self-induced vibration spectrums in order to define limit vibration bands, controllable every cycle or connected to permanent vibration-monitoring systems able to adjust sensible process variables identified by ANOVA, once the vibration readings exceed established quality limits.

[Diversity and frequency of scientific research design and statistical methods in the "Arquivos Brasileiros de Oftalmologia": a systematic review of the "Arquivos Brasileiros de Oftalmologia"--1993-2002].

PubMed

Crosta, Fernando; Nishiwaki-Dantas, Maria Cristina; Silvino, Wilmar; Dantas, Paulo Elias Correa

2005-01-01

To verify the frequency of study design, applied statistical analysis and approval by institutional review offices (Ethics Committee) of articles published in the "Arquivos Brasileiros de Oftalmologia" during a 10-year interval, with later comparative and critical analysis by some of the main international journals in the field of Ophthalmology. Systematic review without metanalysis was performed. Scientific papers published in the "Arquivos Brasileiros de Oftalmologia" between January 1993 and December 2002 were reviewed by two independent reviewers and classified according to the applied study design, statistical analysis and approval by the institutional review offices. To categorize those variables, a descriptive statistical analysis was used. After applying inclusion and exclusion criteria, 584 articles for evaluation of statistical analysis and, 725 articles for evaluation of study design were reviewed. Contingency table (23.10%) was the most frequently applied statistical method, followed by non-parametric tests (18.19%), Student's t test (12.65%), central tendency measures (10.60%) and analysis of variance (9.81%). Of 584 reviewed articles, 291 (49.82%) presented no statistical analysis. Observational case series (26.48%) was the most frequently used type of study design, followed by interventional case series (18.48%), observational case description (13.37%), non-random clinical study (8.96%) and experimental study (8.55%). We found a higher frequency of observational clinical studies, lack of statistical analysis in almost half of the published papers. Increase in studies with approval by institutional review Ethics Committee was noted since it became mandatory in 1996.

Tools for Basic Statistical Analysis

NASA Technical Reports Server (NTRS)

Luz, Paul L.

2005-01-01

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

Statistical summaries of selected Iowa streamflow data through September 2013.

DOT National Transportation Integrated Search

2015-01-01

Statistical summaries of streamflow data collected at : 184 streamgages in Iowa are presented in this report. All : streamgages included for analysis have at least 10 years of : continuous record collected before or through September : 2013. This rep...

Statistical Analysis of Deflation in Covariance and Resultant Pc Values for AQUA, AURA and TERRA

NASA Technical Reports Server (NTRS)

Hasan, Syed O.

2016-01-01

This presentation will display statistical analysis performed for raw conjunction CDMs received for the EOS Aqua, Aura and Terra satellites within the period of February 2015 through July 2016. The analysis performed indicates a discernable deflation in covariance calculated at the JSpOC after the utilization of the dynamic drag consider parameter was implemented operationally in May 2015. As a result, the overall diminution in the conjunction plane intersection of the primary and secondary objects appears to be leading to reduced probability of collision (Pc) values for these conjunction events. This presentation also displays evidence for this theory with analysis of Pc trending plots using data calculated by the SpaceNav CRMS system.

SSD for R: A Comprehensive Statistical Package to Analyze Single-System Data

ERIC Educational Resources Information Center

Auerbach, Charles; Schudrich, Wendy Zeitlin

2013-01-01

The need for statistical analysis in single-subject designs presents a challenge, as analytical methods that are applied to group comparison studies are often not appropriate in single-subject research. "SSD for R" is a robust set of statistical functions with wide applicability to single-subject research. It is a comprehensive package…

A Flexible Approach for the Statistical Visualization of Ensemble Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Potter, K.; Wilson, A.; Bremer, P.

2009-09-29

Scientists are increasingly moving towards ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using multiple numerical models, sampled input conditions and perturbed parameters. While ensemble data sets are a powerful tool for mitigating uncertainty, they pose significant visualization and analysis challenges due to their complexity. We present a collection of overview and statistical displays linked through a high level of interactivity to provide a framework for gaining key scientific insight into the distribution of the simulation results as well as the uncertainty associated with the data. In contrast to methodsmore » that present large amounts of diverse information in a single display, we argue that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis. We demonstrate this approach using driving problems from climate modeling and meteorology and discuss generalizations to other fields.« less

Toward improved analysis of concentration data: Embracing nondetects.

PubMed

Shoari, Niloofar; Dubé, Jean-Sébastien

2018-03-01

Various statistical tests on concentration data serve to support decision-making regarding characterization and monitoring of contaminated media, assessing exposure to a chemical, and quantifying the associated risks. However, the routine statistical protocols cannot be directly applied because of challenges arising from nondetects or left-censored observations, which are concentration measurements below the detection limit of measuring instruments. Despite the existence of techniques based on survival analysis that can adjust for nondetects, these are seldom taken into account properly. A comprehensive review of the literature showed that managing policies regarding analysis of censored data do not always agree and that guidance from regulatory agencies may be outdated. Therefore, researchers and practitioners commonly resort to the most convenient way of tackling the censored data problem by substituting nondetects with arbitrary constants prior to data analysis, although this is generally regarded as a bias-prone approach. Hoping to improve the interpretation of concentration data, the present article aims to familiarize researchers in different disciplines with the significance of left-censored observations and provides theoretical and computational recommendations (under both frequentist and Bayesian frameworks) for adequate analysis of censored data. In particular, the present article synthesizes key findings from previous research with respect to 3 noteworthy aspects of inferential statistics: estimation of descriptive statistics, hypothesis testing, and regression analysis. Environ Toxicol Chem 2018;37:643-656. © 2017 SETAC. © 2017 SETAC.

Statistical properties of filtered pseudorandom digital sequences formed from the sum of maximum-length sequences

NASA Technical Reports Server (NTRS)

Wallace, G. R.; Weathers, G. D.; Graf, E. R.

1973-01-01

The statistics of filtered pseudorandom digital sequences called hybrid-sum sequences, formed from the modulo-two sum of several maximum-length sequences, are analyzed. The results indicate that a relation exists between the statistics of the filtered sequence and the characteristic polynomials of the component maximum length sequences. An analysis procedure is developed for identifying a large group of sequences with good statistical properties for applications requiring the generation of analog pseudorandom noise. By use of the analysis approach, the filtering process is approximated by the convolution of the sequence with a sum of unit step functions. A parameter reflecting the overall statistical properties of filtered pseudorandom sequences is derived. This parameter is called the statistical quality factor. A computer algorithm to calculate the statistical quality factor for the filtered sequences is presented, and the results for two examples of sequence combinations are included. The analysis reveals that the statistics of the signals generated with the hybrid-sum generator are potentially superior to the statistics of signals generated with maximum-length generators. Furthermore, fewer calculations are required to evaluate the statistics of a large group of hybrid-sum generators than are required to evaluate the statistics of the same size group of approximately equivalent maximum-length sequences.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

PubMed

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

Analysis of Sensitivity Experiments - An Expanded Primer

DTIC Science & Technology

2017-03-08

diehard practitioners. The difficulty associated with mastering statistical inference presents a true dilemma. Statistics is an extremely applied...lost, perhaps forever. In other words, when on this safari, you need a guide. This report is designed to be a guide, of sorts. It focuses on analytical...estimated accurately if our analysis is to have real meaning. For this reason, the sensitivity test procedure is designed to concentrate measurements

Dark matter constraints from a joint analysis of dwarf Spheroidal galaxy observations with VERITAS

DOE PAGES

Archambault, S.; Archer, A.; Benbow, W.; ...

2017-04-05

We present constraints on the annihilation cross section of weakly interacting massive particles dark matter based on the joint statistical analysis of four dwarf galaxies with VERITAS. These results are derived from an optimized photon weighting statistical technique that improves on standard imaging atmospheric Cherenkov telescope (IACT) analyses by utilizing the spectral and spatial properties of individual photon events.

Autocorrelation and cross-correlation in time series of homicide and attempted homicide

NASA Astrophysics Data System (ADS)

Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

2014-04-01

We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

Meta-analysis of diagnostic test data: a bivariate Bayesian modeling approach.

PubMed

Verde, Pablo E

2010-12-30

In the last decades, the amount of published results on clinical diagnostic tests has expanded very rapidly. The counterpart to this development has been the formal evaluation and synthesis of diagnostic results. However, published results present substantial heterogeneity and they can be regarded as so far removed from the classical domain of meta-analysis, that they can provide a rather severe test of classical statistical methods. Recently, bivariate random effects meta-analytic methods, which model the pairs of sensitivities and specificities, have been presented from the classical point of view. In this work a bivariate Bayesian modeling approach is presented. This approach substantially extends the scope of classical bivariate methods by allowing the structural distribution of the random effects to depend on multiple sources of variability. Meta-analysis is summarized by the predictive posterior distributions for sensitivity and specificity. This new approach allows, also, to perform substantial model checking, model diagnostic and model selection. Statistical computations are implemented in the public domain statistical software (WinBUGS and R) and illustrated with real data examples. Copyright © 2010 John Wiley & Sons, Ltd.

Technical Brief for the final report presentation for Statistical summaries of selected Iowa streamflow data through September 2013, U.S. Geological Survey Open-File Report 2015-1214, Iowa DOT Research Project TR-669.

DOT National Transportation Integrated Search

2015-01-01

Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is a...

Enhancing the Teaching of Statistics: Portfolio Theory, an Application of Statistics in Finance

ERIC Educational Resources Information Center

Christou, Nicolas

2008-01-01

In this paper we present an application of statistics using real stock market data. Most, if not all, students have some familiarity with the stock market (or at least they have heard about it) and therefore can understand the problem easily. It is the real data analysis that students find interesting. Here we explore the building of efficient…

Introduction to Statistics. Learning Packages in the Policy Sciences Series, PS-26. Revised Edition.

ERIC Educational Resources Information Center

Policy Studies Associates, Croton-on-Hudson, NY.

The primary objective of this booklet is to introduce students to basic statistical skills that are useful in the analysis of public policy data. A few, selected statistical methods are presented, and theory is not emphasized. Chapter 1 provides instruction for using tables, bar graphs, bar graphs with grouped data, trend lines, pie diagrams,…

Uncertainty Analysis for DAM Projects.

DTIC Science & Technology

1987-09-01

overwhelming majority of articles published on the use of statistical methodology for geotechnical engineering focus on performance predictions and design ...Results of the present study do not support the adoption of more esoteric statistical procedures except on a special case basis or in research ...influence that recommended statistical procedures might have had on the Carters Project, had they been applied during planning and design phases

An Investigation of the Overlap Between the Statistical Discrete Gust and the Power Spectral Density Analysis Methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

The results of a NASA investigation of a claimed Overlap between two gust response analysis methods: the Statistical Discrete Gust (SDG) Method and the Power Spectral Density (PSD) Method are presented. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented for several different airplanes at several different flight conditions indicate that such an Overlap does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Crop identification technology assessment for remote sensing. (CITARS) Volume 9: Statistical analysis of results

NASA Technical Reports Server (NTRS)

Davis, B. J.; Feiveson, A. H.

1975-01-01

Results are presented of CITARS data processing in raw form. Tables of descriptive statistics are given along with descriptions and results of inferential analyses. The inferential results are organized by questions which CITARS was designed to answer.

A new statistical methodology predicting chip failure probability considering electromigration

NASA Astrophysics Data System (ADS)

Sun, Ted

In this research thesis, we present a new approach to analyze chip reliability subject to electromigration (EM) whose fundamental causes and EM phenomenon happened in different materials are presented in this thesis. This new approach utilizes the statistical nature of EM failure in order to assess overall EM risk. It includes within-die temperature variations from the chip's temperature map extracted by an Electronic Design Automation (EDA) tool to estimate the failure probability of a design. Both the power estimation and thermal analysis are performed in the EDA flow. We first used the traditional EM approach to analyze the design with a single temperature across the entire chip that involves 6 metal and 5 via layers. Next, we used the same traditional approach but with a realistic temperature map. The traditional EM analysis approach and that coupled with a temperature map and the comparison between the results of considering and not considering temperature map are presented in in this research. A comparison between these two results confirms that using a temperature map yields a less pessimistic estimation of the chip's EM risk. Finally, we employed the statistical methodology we developed considering a temperature map and different use-condition voltages and frequencies to estimate the overall failure probability of the chip. The statistical model established considers the scaling work with the usage of traditional Black equation and four major conditions. The statistical result comparisons are within our expectations. The results of this statistical analysis confirm that the chip level failure probability is higher i) at higher use-condition frequencies for all use-condition voltages, and ii) when a single temperature instead of a temperature map across the chip is considered. In this thesis, I start with an overall review on current design types, common flows, and necessary verifications and reliability checking steps used in this IC design industry. Furthermore, the important concepts about "Scripting Automation" which is used in all the integration of using diversified EDA tools in this research work are also described in detail with several examples and my completed coding works are also put in the appendix for your reference. Hopefully, this construction of my thesis will give readers a thorough understanding about my research work from the automation of EDA tools to the statistical data generation, from the nature of EM to the statistical model construction, and the comparisons among the traditional EM analysis and the statistical EM analysis approaches.

Web 2.0 Articles: Content Analysis and a Statistical Model to Predict Recognition of the Need for New Instructional Design Strategies

ERIC Educational Resources Information Center

Liu, Leping; Maddux, Cleborne D.

2008-01-01

This article presents a study of Web 2.0 articles intended to (a) analyze the content of what is written and (b) develop a statistical model to predict whether authors' write about the need for new instructional design strategies and models. Eighty-eight technology articles were subjected to lexical analysis and a logistic regression model was…

Comparisons of non-Gaussian statistical models in DNA methylation analysis.

PubMed

Ma, Zhanyu; Teschendorff, Andrew E; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-06-16

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance.

Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

PubMed Central

Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-01-01

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

PubMed Central

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

Determining Differences in Efficacy of Two Disinfectants Using t-Tests.

ERIC Educational Resources Information Center

Brehm, Michael A.; And Others

1996-01-01

Presents an experiment to compare the effectiveness of 95% ethanol to 20% bleach as disinfectants using t-tests for the statistical analysis of the data. Reports that bleach is a better disinfectant. Discusses the statistical and practical significance of the results. (JRH)

Research Design and Statistics for Applied Linguistics.

ERIC Educational Resources Information Center

Hatch, Evelyn; Farhady, Hossein

An introduction to the conventions of research design and statistical analysis is presented for graduate students of applied linguistics. The chapters cover such concepts as the definition of research, variables, research designs, research report formats, sorting and displaying data, probability and hypothesis testing, comparing means,…

Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines

NASA Astrophysics Data System (ADS)

Francom, D.; Sansó, B.; Bulaevskaya, V.; Lucas, D. D.

2016-12-01

Uncertainty in the inputs of complex computer models, including atmospheric dispersion and transport codes, is often assessed via statistical surrogate models. Surrogate models are computationally efficient statistical approximations of expensive computer models that enable uncertainty analysis. We introduce Bayesian adaptive spline methods for producing surrogate models that capture the major spatiotemporal patterns of the parent model, while satisfying all the necessities of flexibility, accuracy and computational feasibility. We present novel methodological and computational approaches motivated by a controlled atmospheric tracer release experiment conducted at the Diablo Canyon nuclear power plant in California. Traditional methods for building statistical surrogate models often do not scale well to experiments with large amounts of data. Our approach is well suited to experiments involving large numbers of model inputs, large numbers of simulations, and functional output for each simulation. Our approach allows us to perform global sensitivity analysis with ease. We also present an approach to calibration of simulators using field data.

Statistical summaries of selected Iowa streamflow data through September 2013

USGS Publications Warehouse

Eash, David A.; O'Shea, Padraic S.; Weber, Jared R.; Nguyen, Kevin T.; Montgomery, Nicholas L.; Simonson, Adrian J.

2016-01-04

Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study.

PubMed

MacLean, Adam L; Harrington, Heather A; Stumpf, Michael P H; Byrne, Helen M

2016-01-01

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non-exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

A new u-statistic with superior design sensitivity in matched observational studies.

PubMed

Rosenbaum, Paul R

2011-09-01

In an observational or nonrandomized study of treatment effects, a sensitivity analysis indicates the magnitude of bias from unmeasured covariates that would need to be present to alter the conclusions of a naïve analysis that presumes adjustments for observed covariates suffice to remove all bias. The power of sensitivity analysis is the probability that it will reject a false hypothesis about treatment effects allowing for a departure from random assignment of a specified magnitude; in particular, if this specified magnitude is "no departure" then this is the same as the power of a randomization test in a randomized experiment. A new family of u-statistics is proposed that includes Wilcoxon's signed rank statistic but also includes other statistics with substantially higher power when a sensitivity analysis is performed in an observational study. Wilcoxon's statistic has high power to detect small effects in large randomized experiments-that is, it often has good Pitman efficiency-but small effects are invariably sensitive to small unobserved biases. Members of this family of u-statistics that emphasize medium to large effects can have substantially higher power in a sensitivity analysis. For example, in one situation with 250 pair differences that are Normal with expectation 1/2 and variance 1, the power of a sensitivity analysis that uses Wilcoxon's statistic is 0.08 while the power of another member of the family of u-statistics is 0.66. The topic is examined by performing a sensitivity analysis in three observational studies, using an asymptotic measure called the design sensitivity, and by simulating power in finite samples. The three examples are drawn from epidemiology, clinical medicine, and genetic toxicology. © 2010, The International Biometric Society.

[Bayesian statistics in medicine -- part II: main applications and inference].

PubMed

Montomoli, C; Nichelatti, M

2008-01-01

Bayesian statistics is not only used when one is dealing with 2-way tables, but it can be used for inferential purposes. Using the basic concepts presented in the first part, this paper aims to give a simple overview of Bayesian methods by introducing its foundation (Bayes' theorem) and then applying this rule to a very simple practical example; whenever possible, the elementary processes at the basis of analysis are compared to those of frequentist (classical) statistical analysis. The Bayesian reasoning is naturally connected to medical activity, since it appears to be quite similar to a diagnostic process.

Use of statistical study methods for the analysis of the results of the imitation modeling of radiation transfer

NASA Astrophysics Data System (ADS)

Alekseenko, M. A.; Gendrina, I. Yu.

2017-11-01

Recently, due to the abundance of various types of observational data in the systems of vision through the atmosphere and the need for their processing, the use of various methods of statistical research in the study of such systems as correlation-regression analysis, dynamic series, variance analysis, etc. is actual. We have attempted to apply elements of correlation-regression analysis for the study and subsequent prediction of the patterns of radiation transfer in these systems same as in the construction of radiation models of the atmosphere. In this paper, we present some results of statistical processing of the results of numerical simulation of the characteristics of vision systems through the atmosphere obtained with the help of a special software package.1

Transfusion Indication Threshold Reduction (TITRe2) randomized controlled trial in cardiac surgery: statistical analysis plan.

PubMed

Pike, Katie; Nash, Rachel L; Murphy, Gavin J; Reeves, Barnaby C; Rogers, Chris A

2015-02-22

The Transfusion Indication Threshold Reduction (TITRe2) trial is the largest randomized controlled trial to date to compare red blood cell transfusion strategies following cardiac surgery. This update presents the statistical analysis plan, detailing how the study will be analyzed and presented. The statistical analysis plan has been written following recommendations from the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, prior to database lock and the final analysis of trial data. Outlined analyses are in line with the Consolidated Standards of Reporting Trials (CONSORT). The study aims to randomize 2000 patients from 17 UK centres. Patients are randomized to either a restrictive (transfuse if haemoglobin concentration <7.5 g/dl) or liberal (transfuse if haemoglobin concentration <9 g/dl) transfusion strategy. The primary outcome is a binary composite outcome of any serious infectious or ischaemic event in the first 3 months following randomization. The statistical analysis plan details how non-adherence with the intervention, withdrawals from the study, and the study population will be derived and dealt with in the analysis. The planned analyses of the trial primary and secondary outcome measures are described in detail, including approaches taken to deal with multiple testing, model assumptions not being met and missing data. Details of planned subgroup and sensitivity analyses and pre-specified ancillary analyses are given, along with potential issues that have been identified with such analyses and possible approaches to overcome such issues. ISRCTN70923932 .

Preparing and Presenting Effective Research Posters

PubMed Central

Miller, Jane E

2007-01-01

Objectives Posters are a common way to present results of a statistical analysis, program evaluation, or other project at professional conferences. Often, researchers fail to recognize the unique nature of the format, which is a hybrid of a published paper and an oral presentation. This methods note demonstrates how to design research posters to convey study objectives, methods, findings, and implications effectively to varied professional audiences. Methods A review of existing literature on research communication and poster design is used to identify and demonstrate important considerations for poster content and layout. Guidelines on how to write about statistical methods, results, and statistical significance are illustrated with samples of ineffective writing annotated to point out weaknesses, accompanied by concrete examples and explanations of improved presentation. A comparison of the content and format of papers, speeches, and posters is also provided. Findings Each component of a research poster about a quantitative analysis should be adapted to the audience and format, with complex statistical results translated into simplified charts, tables, and bulleted text to convey findings as part of a clear, focused story line. Conclusions Effective research posters should be designed around two or three key findings with accompanying handouts and narrative description to supply additional technical detail and encourage dialog with poster viewers. PMID:17355594

Illinois Kids Count: A Snap Shot of Our Future. County by County Profiles of Child Well-Being '92.

ERIC Educational Resources Information Center

Voices for Illinois Children, Chicago.

This booklet presents statistics concerning the well-being of Illinois' 3.3 million children between 1980 and 1990. Statistics are compared county by county for each of the state's 102 counties, and statewide statistics are compared with those of the entire nation. A statewide analysis focuses on spending per pupil on education, the percentage of…

The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

NASA Astrophysics Data System (ADS)

Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

2017-04-01

Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the apparent benefit from using ensembles for cloudy radiance assimilation in an EnVar context.

An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data.

PubMed

Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John

2018-03-07

DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.

Lognormal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of α-Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2010-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086

Characterizing microstructural features of biomedical samples by statistical analysis of Mueller matrix images

NASA Astrophysics Data System (ADS)

He, Honghui; Dong, Yang; Zhou, Jialing; Ma, Hui

2017-03-01

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

Transition-Region Ultraviolet Explosive Events in IRIS Si IV: A Statistical Analysis

NASA Astrophysics Data System (ADS)

Bartz, Allison

2018-01-01

Explosive events (EEs) in the solar transition region are characterized by broad, non-Gaussian line profiles with wings at Doppler velocities exceeding the speed of sound. We present a statistical analysis of 23 IRIS (Interface Region Imaging Spectrograph) sit-and-stare observations, observed between April 2014 and March 2017. Using the IRIS Si IV 1394 Å and 1403 Å spectral windows and the 1400Å Slit Jaw images we have identified 581 EEs. We found that most EEs last less than 20 min. and have a spatial scale on the slit less than 10”, agreeing with measurements in previous work. We observed most EEs in active regions, regardless of date of observation, but selection bias of IRIS observations cannot be ruled out. We also present preliminary findings of optical depth effects from our statistical study.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Statistical analysis of Skylab 3. [endocrine/metabolic studies of astronauts

NASA Technical Reports Server (NTRS)

Johnston, D. A.

1974-01-01

The results of endocrine/metabolic studies of astronauts on Skylab 3 are reported. One-way analysis of variance, contrasts, two-way unbalanced analysis of variance, and analysis of periodic changes in flight are included. Results for blood tests, and urine tests are presented.

Trend Analysis Using Microcomputers.

ERIC Educational Resources Information Center

Berger, Carl F.

A trend analysis statistical package and additional programs for the Apple microcomputer are presented. They illustrate strategies of data analysis suitable to the graphics and processing capabilities of the microcomputer. The programs analyze data sets using examples of: (1) analysis of variance with multiple linear regression; (2) exponential…

A Divergence Statistics Extension to VTK for Performance Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pebay, Philippe Pierre; Bennett, Janine Camille

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,more » "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.« less

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

NASA Technical Reports Server (NTRS)

Chao, Luen-Yuan; Shetty, Dinesh K.

1992-01-01

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Economic and statistical analysis of time limitations for spotting fluids and fishing operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, P.S.; Brinkmann, P.E.; Taneja, P.K.

1984-05-01

This paper reviews the statistics of ''Spotting Fluids'' to free stuck drill pipe as well as the economics and statistics of drill string fishing operations. Data were taken from Mobil Oil Exploration and Producing Southeast Inc.'s (MOEPSI) records from 1970-1981. Only those events which occur after a drill string becomes stuck are discussed. The data collected were categorized as Directional Wells and Straight Wells. Bar diagrams are presented to show the Success Ratio vs. Soaking Time for each of the two categories. An analysis was made to identify the elapsed time limit to place the spotting fluid for maximum probabilitymore » of success. Also determined was the statistical minimum soaking time and the maximum soaking time. For determining the time limit for fishing operations, the following criteria were used: 1. The Risked ''Economic Breakeven Analysis'' concept was developed based on the work of Harrison. 2. Statistical Probability of Success based on MOEPSI's records from 1970-1981.« less

Influence of nonlinear effects on statistical properties of the radiation from SASE FEL

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-02-01

The paper presents analysis of statistical properties of the radiation from self-amplified spontaneous emission (SASE) free-electron laser operating in nonlinear mode. The present approach allows one to calculate the following statistical properties of the SASE FEL radiation: time and spectral field correlation functions, distribution of the fluctuations of the instantaneous radiation power, distribution of the energy in the electron bunch, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and the radiation spectrum. It has been observed that the statistics of the instantaneous radiation power from SASE FEL operating in the nonlinear regime changes significantly with respect to the linear regime. All numerical results presented in the paper have been calculated for the 70 nm SASE FEL at the TESLA Test Facility under construction at DESY.

Wavelet analysis of polarization azimuths maps for laser images of myocardial tissue for the purpose of diagnosing acute coronary insufficiency

NASA Astrophysics Data System (ADS)

Wanchuliak, O. Ya.; Peresunko, A. P.; Bakko, Bouzan Adel; Kushnerick, L. Ya.

2011-09-01

This paper presents the foundations of a large scale - localized wavelet - polarization analysis - inhomogeneous laser images of histological sections of myocardial tissue. Opportunities were identified defining relations between the structures of wavelet coefficients and causes of death. The optical model of polycrystalline networks of myocardium protein fibrils is presented. The technique of determining the coordinate distribution of polarization azimuth of the points of laser images of myocardium histological sections is suggested. The results of investigating the interrelation between the values of statistical (statistical moments of the 1st-4th order) parameters are presented which characterize distributions of wavelet - coefficients polarization maps of myocardium layers and death reasons.

A statistical analysis of IUE spectra of dwarf novae and nova-like stars

NASA Technical Reports Server (NTRS)

Ladous, Constanze

1990-01-01

First results of a statistical analysis of the IUE International Ultraviolet Explorer archive on dwarf novae and nova like stars are presented. The archive contains approximately 2000 low resolution spectra of somewhat over 100 dwarf novae and nova like stars. Many of these were looked at individually, but so far the collective information content of this set of data has not been explored. The first results of work are reported.

Statistical assessment on a combined analysis of GRYN-ROMN-UCBN upland vegetation vital signs

USGS Publications Warehouse

Irvine, Kathryn M.; Rodhouse, Thomas J.

2014-01-01

As of 2013, Rocky Mountain and Upper Columbia Basin Inventory and Monitoring Networks have multiple years of vegetation data and Greater Yellowstone Network has three years of vegetation data and monitoring is ongoing in all three networks. Our primary objective is to assess whether a combined analysis of these data aimed at exploring correlations with climate and weather data is feasible. We summarize the core survey design elements across protocols and point out the major statistical challenges for a combined analysis at present. The dissimilarity in response designs between ROMN and UCBN-GRYN network protocols presents a statistical challenge that has not been resolved yet. However, the UCBN and GRYN data are compatible as they implement a similar response design; therefore, a combined analysis is feasible and will be pursued in future. When data collected by different networks are combined, the survey design describing the merged dataset is (likely) a complex survey design. A complex survey design is the result of combining datasets from different sampling designs. A complex survey design is characterized by unequal probability sampling, varying stratification, and clustering (see Lohr 2010 Chapter 7 for general overview). Statistical analysis of complex survey data requires modifications to standard methods, one of which is to include survey design weights within a statistical model. We focus on this issue for a combined analysis of upland vegetation from these networks, leaving other topics for future research. We conduct a simulation study on the possible effects of equal versus unequal probability selection of points on parameter estimates of temporal trend using available packages within the R statistical computing package. We find that, as written, using lmer or lm for trend detection in a continuous response and clm and clmm for visually estimated cover classes with “raw” GRTS design weights specified for the weight argument leads to substantially different results and/or computational instability. However, when only fixed effects are of interest, the survey package (svyglm and svyolr) may be suitable for a model-assisted analysis for trend. We provide possible directions for future research into combined analysis for ordinal and continuous vital sign indictors.

Algorithm for Identifying Erroneous Rain-Gauge Readings

NASA Technical Reports Server (NTRS)

Rickman, Doug

2005-01-01

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

An investigation of the 'Overlap' between the Statistical-Discrete-Gust and the Power-Spectral-Density analysis methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

This paper presents the results of a NASA investigation of a claimed 'Overlap' between two gust response analysis methods: the Statistical Discrete Gust (SDG) method and the Power Spectral Density (PSD) method. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented in this paper for several different airplanes at several different flight conditions indicate that such an 'Overlap' does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Applications of the DOE/NASA wind turbine engineering information system

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Spera, D. A.

1981-01-01

A statistical analysis of data obtained from the Technology and Engineering Information Systems was made. The systems analyzed consist of the following elements: (1) sensors which measure critical parameters (e.g., wind speed and direction, output power, blade loads and component vibrations); (2) remote multiplexing units (RMUs) on each wind turbine which frequency-modulate, multiplex and transmit sensor outputs; (3) on-site instrumentation to record, process and display the sensor output; and (4) statistical analysis of data. Two examples of the capabilities of these systems are presented. The first illustrates the standardized format for application of statistical analysis to each directly measured parameter. The second shows the use of a model to estimate the variability of the rotor thrust loading, which is a derived parameter.

Show the Data, Don't Conceal Them

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2011-01-01

Current standards of data presentation and analysis in biological journals often fall short of ideal. This is the first of a planned series of short articles, to be published in a number of journals, aiming to highlight the principles of clear data presentation and appropriate statistical analysis. This article considers the methods used to show…

Analysis of uncertainties and convergence of the statistical quantities in turbulent wall-bounded flows by means of a physically based criterion

NASA Astrophysics Data System (ADS)

Andrade, João Rodrigo; Martins, Ramon Silva; Thompson, Roney Leon; Mompean, Gilmar; da Silveira Neto, Aristeu

2018-04-01

The present paper provides an analysis of the statistical uncertainties associated with direct numerical simulation (DNS) results and experimental data for turbulent channel and pipe flows, showing a new physically based quantification of these errors, to improve the determination of the statistical deviations between DNSs and experiments. The analysis is carried out using a recently proposed criterion by Thompson et al. ["A methodology to evaluate statistical errors in DNS data of plane channel flows," Comput. Fluids 130, 1-7 (2016)] for fully turbulent plane channel flows, where the mean velocity error is estimated by considering the Reynolds stress tensor, and using the balance of the mean force equation. It also presents how the residual error evolves in time for a DNS of a plane channel flow, and the influence of the Reynolds number on its convergence rate. The root mean square of the residual error is shown in order to capture a single quantitative value of the error associated with the dimensionless averaging time. The evolution in time of the error norm is compared with the final error provided by DNS data of similar Reynolds numbers available in the literature. A direct consequence of this approach is that it was possible to compare different numerical results and experimental data, providing an improved understanding of the convergence of the statistical quantities in turbulent wall-bounded flows.

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

PubMed

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

First Results from the Light and Spectroscopy Concept Inventory

ERIC Educational Resources Information Center

Bardar, Erin M.

2008-01-01

This article presents results from a two-semester field test of the Light and Spectroscopy Concept Inventory (LSCI). Statistical analysis indicates that the LSCI has the sensitivity to measure statistically significant changes in students' understanding of light-related topics due to instruction in introductory astronomy courses and to distinguish…

Effects of atmospheric turbulence on microwave and millimeter wave satellite communications systems. [attenuation statistics and antenna design

NASA Technical Reports Server (NTRS)

Devasirvatham, D. M. J.; Hodge, D. B.

1981-01-01

A model of the microwave and millimeter wave link in the presence of atmospheric turbulence is presented with emphasis on satellite communications systems. The analysis is based on standard methods of statistical theory. The results are directly usable by the design engineer.

Analyzing a Mature Software Inspection Process Using Statistical Process Control (SPC)

NASA Technical Reports Server (NTRS)

Barnard, Julie; Carleton, Anita; Stamper, Darrell E. (Technical Monitor)

1999-01-01

This paper presents a cooperative effort where the Software Engineering Institute and the Space Shuttle Onboard Software Project could experiment applying Statistical Process Control (SPC) analysis to inspection activities. The topics include: 1) SPC Collaboration Overview; 2) SPC Collaboration Approach and Results; and 3) Lessons Learned.

Three Strategies for the Critical Use of Statistical Methods in Psychological Research

ERIC Educational Resources Information Center

Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando

2017-01-01

We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…

Some Statistical Properties of Tonality, 1650-1900

ERIC Educational Resources Information Center

White, Christopher Wm.

2013-01-01

This dissertation investigates the statistical properties present within corpora of common practice music, involving a data set of more than 8,000 works spanning from 1650 to 1900, and focusing specifically on the properties of the chord progressions contained therein. In the first chapter, methodologies concerning corpus analysis are presented…

Application of Transformations in Parametric Inference

ERIC Educational Resources Information Center

Brownstein, Naomi; Pensky, Marianna

2008-01-01

The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: a primer and applications.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E

2014-04-01

This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Environmental justice assessment for transportation : risk analysis

DOT National Transportation Integrated Search

1999-04-01

This paper presents methods of comparing populations and their racial/ethnic compositions using tabulations, histograms, and Chi Squared tests for statistical significance of differences found. Two examples of these methods are presented: comparison ...

Conditional Probability Analysis: A Statistical Tool for Environmental Analysis.

EPA Science Inventory

The use and application of environmental conditional probability analysis (CPA) is relatively recent. The first presentation using CPA was made in 2002 at the New England Association of Environmental Biologists Annual Meeting in Newport. Rhode Island. CPA has been used since the...

[The principal components analysis--method to classify the statistical variables with applications in medicine].

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis.

The Australasian Resuscitation in Sepsis Evaluation (ARISE) trial statistical analysis plan.

PubMed

Delaney, Anthony P; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

2013-09-01

The Australasian Resuscitation in Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the emergency department with severe sepsis. In keeping with current practice, and considering aspects of trial design and reporting specific to non-pharmacological interventions, our plan outlines the principles and methods for analysing and reporting the trial results. The document is prepared before completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and before completion of the two related international studies. Our statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. We reviewed the data collected by the research team as specified in the study protocol and detailed in the study case report form. We describe information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation, other related therapies and other relevant data with appropriate comparisons between groups. We define the primary, secondary and tertiary outcomes for the study, with description of the planned statistical analyses. We have developed a statistical analysis plan with a trial profile, mock-up tables and figures. We describe a plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies and adverse events. We describe the primary, secondary and tertiary outcomes with identification of subgroups to be analysed. We have developed a statistical analysis plan for the ARISE study, available in the public domain, before the completion of recruitment into the study. This will minimise analytical bias and conforms to current best practice in conducting clinical trials.

Sedimentological analysis and bed thickness statistics from a Carboniferous deep-water channel-levee complex: Myall Trough, SE Australia

NASA Astrophysics Data System (ADS)

Palozzi, Jason; Pantopoulos, George; Maravelis, Angelos G.; Nordsvan, Adam; Zelilidis, Avraam

2018-02-01

This investigation presents an outcrop-based integrated study of internal division analysis and statistical treatment of turbidite bed thickness applied to a Carboniferous deep-water channel-levee complex in the Myall Trough, southeast Australia. Turbidite beds of the studied succession are characterized by a range of sedimentary structures grouped into two main associations, a thick-bedded and a thin-bedded one, that reflect channel-fill and overbank/levee deposits, respectively. Three vertically stacked channel-levee cycles have been identified. Results of statistical analysis of bed thickness, grain-size and internal division patterns applied on the studied channel-levee succession, indicate that turbidite bed thickness data seem to be well characterized by a bimodal lognormal distribution, which is possibly reflecting the difference between deposition from lower-density flows (in a levee/overbank setting) and very high-density flows (in a channel fill setting). Power law and exponential distributions were observed to hold only for the thick-bedded parts of the succession and cannot characterize the whole bed thickness range of the studied sediments. The succession also exhibits non-random clustering of bed thickness and grain-size measurements. The studied sediments are also characterized by the presence of statistically detected fining-upward sandstone packets. A novel quantitative approach (change-point analysis) is proposed for the detection of those packets. Markov permutation statistics also revealed the existence of order in the alternation of internal divisions in the succession expressed by an optimal internal division cycle reflecting two main types of gravity flow events deposited within both thick-bedded conglomeratic and thin-bedded sandstone associations. The analytical methods presented in this study can be used as additional tools for quantitative analysis and recognition of depositional environments in hydrocarbon-bearing research of ancient deep-water channel-levee settings.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

PubMed

Hauber, A Brett; González, Juan Marcos; Groothuis-Oudshoorn, Catharina G M; Prior, Thomas; Marshall, Deborah A; Cunningham, Charles; IJzerman, Maarten J; Bridges, John F P

2016-06-01

Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

PubMed

Carroll, Adam J; Badger, Murray R; Harvey Millar, A

2010-07-14

Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.

PV System Component Fault and Failure Compilation and Analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klise, Geoffrey Taylor; Lavrova, Olga; Gooding, Renee Lynne

This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.

Analysis and optimization of indicators of energy and resource consumption of gas turbine and electric drives for transportation of hydrocarbons

NASA Astrophysics Data System (ADS)

Golik, V. V.; Zemenkova, M. Yu; Seroshtanov, I. V.; Begalko, Z. V.

2018-05-01

The paper presents the results of the analysis of statistical indicators of energy and resource consumption in oil and gas transportation by the example of one of the regions of Russia. The article analyzes engineering characteristics of compressor station drives. Official statistical bulletins on the fuel and energy resources of the region in the pipeline oil and gas transportation system were used as the initial data.

Statistical analysis of oil percolation through pressboard measured by optical recording

NASA Astrophysics Data System (ADS)

Rogalski, Przemysław; Kozak, Czesław

2017-08-01

The paper presents a measuring station used to measure the percolation of transformer oil by electrotechnical pressboard. Nytro Taurus insulating oil manufactured by Nynas company percolation rate by the Pucaro company pressboard investigation was made. Approximately 60 samples of Pucaro made pressboard, widely used for insulation of power transformers, was measured. Statistical analysis of oil percolation times were performed. The measurements made it possible to determine the distribution of capillary diameters occurring in the pressboard.

Laser diagnostics of native cervix dabs with human papilloma virus in high carcinogenic risk

NASA Astrophysics Data System (ADS)

Peresunko, O. P.; Karpenko, Ju. G.; Burkovets, D. N.; Ivashko, P. V.; Nikorych, A. V.; Yermolenko, S. B.; Gruia, Ion; Gruia, M. J.

2015-11-01

The results of experimental studies of coordinate distributions of Mueller matrix elements of the following types of cervical scraping tissue are presented: rate- low-grade - highly differentiated dysplasia (CIN1-CIN3) - adenocarcinoma of high, medium and low levels of differentiation (G1-G3). The rationale for the choice of statistical points 1-4 orders polarized coherent radiation field, transformed as a result of interaction with the oncologic modified biological layers "epithelium-stroma" as a quantitative criterion of polarimetric optical differentiation state of human biological tissues are shown here. The analysis of the obtained Mueller matrix elements and statistical correlation methods, the systematized by types studied tissues is accomplished. The results of research images of Mueller matrix elements m34 for this type of pathology as low-grade dysplasia (CIN2), the results of its statistical and correlation analysis are presented.

A note about high blood pressure in childhood

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Simão, Carla

2017-06-01

In medical, behavioral and social sciences it is usual to get a binary outcome. In the present work is collected information where some of the outcomes are binary variables (1='yes'/ 0='no'). In [14] a preliminary study about the caregivers perception of pediatric hypertension was introduced. An experimental questionnaire was designed to be answered by the caregivers of routine pediatric consultation attendees in the Santa Maria's hospital (HSM). The collected data was statistically analyzed, where a descriptive analysis and a predictive model were performed. Significant relations between some socio-demographic variables and the assessed knowledge were obtained. In [14] can be found a statistical data analysis using partial questionnaire's information. The present article completes the statistical approach estimating a model for relevant remaining questions of questionnaire by Generalized Linear Models (GLM). Exploring the binary outcome issue, we intend to extend this approach using Generalized Linear Mixed Models (GLMM), but the process is still ongoing.

Pixel Statistical Analysis of Diabetic vs. Non-diabetic Foot-Sole Spectral Terahertz Reflection Images

NASA Astrophysics Data System (ADS)

Hernandez-Cardoso, G. G.; Alfaro-Gomez, M.; Rojas-Landeros, S. C.; Salas-Gutierrez, I.; Castro-Camus, E.

2018-03-01

In this article, we present a series of hydration mapping images of the foot soles of diabetic and non-diabetic subjects measured by terahertz reflectance. In addition to the hydration images, we present a series of RYG-color-coded (red yellow green) images where pixels are assigned one of the three colors in order to easily identify areas in risk of ulceration. We also present the statistics of the number of pixels with each color as a potential quantitative indicator for diabetic foot-syndrome deterioration.

Analysis and meta-analysis of single-case designs: an introduction.

PubMed

Shadish, William R

2014-04-01

The last 10 years have seen great progress in the analysis and meta-analysis of single-case designs (SCDs). This special issue includes five articles that provide an overview of current work on that topic, including standardized mean difference statistics, multilevel models, Bayesian statistics, and generalized additive models. Each article analyzes a common example across articles and presents syntax or macros for how to do them. These articles are followed by commentaries from single-case design researchers and journal editors. This introduction briefly describes each article and then discusses several issues that must be addressed before we can know what analyses will eventually be best to use in SCD research. These issues include modeling trend, modeling error covariances, computing standardized effect size estimates, assessing statistical power, incorporating more accurate models of outcome distributions, exploring whether Bayesian statistics can improve estimation given the small samples common in SCDs, and the need for annotated syntax and graphical user interfaces that make complex statistics accessible to SCD researchers. The article then discusses reasons why SCD researchers are likely to incorporate statistical analyses into their research more often in the future, including changing expectations and contingencies regarding SCD research from outside SCD communities, changes and diversity within SCD communities, corrections of erroneous beliefs about the relationship between SCD research and statistics, and demonstrations of how statistics can help SCD researchers better meet their goals. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Shaping the Marketers of Tomorrow: An Analysis of 25 Years of Marketing Education Review

ERIC Educational Resources Information Center

Morrison, Stacey A.; Blair, Amanda J.; McMullan, Kylie L.; Flostrand, Andrew

2017-01-01

This article presents a bibliometric analysis of "Marketing Education Review" from its inception in 1990 until 2014. A brief history of the journal is presented and its content is analyzed. In total, 706 articles were studied in terms of their authorship, manuscript, and content characteristics. Descriptive statistics provide an overview…

Data analysis report on ATS-F COMSAT millimeter wave propagation experiment, part 1. [effects of hydrometeors on ground to satellite communication

NASA Technical Reports Server (NTRS)

Hyde, G.

1976-01-01

The 13/18 GHz COMSAT Propagation Experiment (CPE) was performed to measure attenuation caused by hydrometeors along slant paths from transmitting terminals on the ground to the ATS-6 satellite. The effectiveness of site diversity in overcoming this impairment was also studied. Problems encountered in assembling a valid data base of rain induced attenuation data for statistical analysis are considered. The procedures used to obtain the various statistics are then outlined. The graphs and tables of statistical data for the 15 dual frequency (13 and 18 GHz) site diversity locations are discussed. Cumulative rain rate statistics for the Fayetteville and Boston sites based on point rainfall data collected are presented along with extrapolations of the attenuation and point rainfall data.

An Analysis of Research Trends in Dissertations and Theses Studying Blended Learning

ERIC Educational Resources Information Center

Drysdale, Jeffery S.; Graham, Charles R.; Spring, Kristian J.; Halverson, Lisa R.

2013-01-01

This article analyzes the research of 205 doctoral dissertations and masters' theses in the domain of blended learning. A summary of trends regarding the growth and context of blended learning research is presented. Methodological trends are described in terms of qualitative, inferential statistics, descriptive statistics, and combined approaches…

Teaching Guide for "The Environmental Data Book: A Guide to Statistics on the Environment and Development."

ERIC Educational Resources Information Center

Sheram, Katherine

This teaching guide accompanies "The Environmental Data Book," published by the World Bank. Environmental and development statistics are presented for discussion and analysis. Indicators of environmental quality and economic development are defined with accompanying charts and maps. Activities accompany each lesson, along with a worksheet at the…

Publishing in "SERJ": An Analysis of Papers from 2002-2009

ERIC Educational Resources Information Center

Zieffler, Andrew; Garfield, Joan; delMas, Robert C.; Le, Laura; Isaak, Rebekah; Bjornsdottir, Audbjorg; Park, Jiyoon

2011-01-01

"SERJ" has provided a high quality professional publication venue for researchers in statistics education for close to a decade. This paper presents a review of the articles published to explore what they suggest about the field of statistics education, the researchers, the questions addressed, and the growing knowledge base on teaching and…

[Artificial neural networks for decision making in urologic oncology].

PubMed

Remzi, M; Djavan, B

2007-06-01

This chapter presents a detailed introduction regarding Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. It includes a description of ANNs methodology and points out the differences between Artifical Intelligence and traditional statistic models in terms of usefulness for patients and clinicians, and its advantages over current statistical analysis.

Statistical properties of alternative national forest inventory area estimators

Treesearch

Francis Roesch; John Coulston; Andrew D. Hill

2012-01-01

The statistical properties of potential estimators of forest area for the USDA Forest Service's Forest Inventory and Analysis (FIA) program are presented and discussed. The current FIA area estimator is compared and contrasted with a weighted mean estimator and an estimator based on the Polya posterior, in the presence of nonresponse. Estimator optimality is...

Statistics Test Questions: Content and Trends

ERIC Educational Resources Information Center

Salcedo, Audy

2014-01-01

This study presents the results of the analysis of a group of teacher-made test questions for statistics courses at the university level. Teachers were asked to submit tests they had used in their previous two semesters. Ninety-seven tests containing 978 questions were gathered and classified according to the SOLO taxonomy (Biggs & Collis,…

Statistical basis and outputs of stable isotope mixing models: Comment on Fry (2013)

EPA Science Inventory

A recent article by Fry (2013; Mar Ecol Prog Ser 472:1−13) reviewed approaches to solving underdetermined stable isotope mixing systems, and presented a new graphical approach and set of summary statistics for the analysis of such systems. In his review, Fry (2013) mis-characteri...

"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…

[Statistical considerations of isolated maxillofacial fractures in Sao Paulo].

PubMed

Crivello, O; Luz, J G; Lemos, J B; Rezende, J R

1989-01-01

Statistical analysis of 550 isolated maxillo-facial fractures is presented. Data obtained illustrated the important number of maxillo-facial fractures in Sao Paulo, the automobilistics accidents were responsible for most maxillo-facial trauma, the jaw and the malar were more predominant than the others structures and the conservative treatment was the most used one.

Nebraska's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; Dacia M. Meneguzzo; Charles J. Barnett

2011-01-01

The first full annual inventory of Nebraska's forests was completed in 2005 after 8,335 plots were selected and 274 forested plots were visited and measured. This report includes detailed information on forest inventory methods, and data quality estimates. Tables of various important resource statistics are presented. Detailed analysis of the inventory data are...

Kansas's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; W. Keith Moser; Charles J. Barnett

2011-01-01

The first full annual inventory of Kansas's forests was completed in 2005 after 8,868 plots were selected and 468 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of Kansas inventory is presented...

Advance Report of Final Mortality Statistics, 1985.

ERIC Educational Resources Information Center

Monthly Vital Statistics Report, 1987

1987-01-01

This document presents mortality statistics for 1985 for the entire United States. Data analysis and discussion of these factors is included: death and death rates; death rates by age, sex, and race; expectation of life at birth and at specified ages; causes of death; infant mortality; and maternal mortality. Highlights reported include: (1) the…

The Dark Side of the Tube

ERIC Educational Resources Information Center

Wagler, Amy; Wagler, Ron

2014-01-01

Every high school graduate should be able to use data analysis and statistical reasoning to draw conclusions about the world. Two core statistical concepts for students to understand are the role of variability in measures and evaluating the effect of a variable. In the activity presented in this article, students investigate a scientific question…

High order statistical signatures from source-driven measurements of subcritical fissile systems

NASA Astrophysics Data System (ADS)

Mattingly, John Kelly

1998-11-01

This research focuses on the development and application of high order statistical analyses applied to measurements performed with subcritical fissile systems driven by an introduced neutron source. The signatures presented are derived from counting statistics of the introduced source and radiation detectors that observe the response of the fissile system. It is demonstrated that successively higher order counting statistics possess progressively higher sensitivity to reactivity. Consequently, these signatures are more sensitive to changes in the composition, fissile mass, and configuration of the fissile assembly. Furthermore, it is shown that these techniques are capable of distinguishing the response of the fissile system to the introduced source from its response to any internal or inherent sources. This ability combined with the enhanced sensitivity of higher order signatures indicates that these techniques will be of significant utility in a variety of applications. Potential applications include enhanced radiation signature identification of weapons components for nuclear disarmament and safeguards applications and augmented nondestructive analysis of spent nuclear fuel. In general, these techniques expand present capabilities in the analysis of subcritical measurements.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

PubMed

Harrigan, George G; Harrison, Jay M

2012-01-01

New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

Mathematics and statistics research progress report, period ending June 30, 1983

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beauchamp, J. J.; Denson, M. V.; Heath, M. T.

1983-08-01

This report is the twenty-sixth in the series of progress reports of Mathematics and Statistics Research of the Computer Sciences organization, Union Carbide Corporation Nuclear Division. Part A records research progress in analysis of large data sets, applied analysis, biometrics research, computational statistics, materials science applications, numerical linear algebra, and risk analysis. Collaboration and consulting with others throughout the Oak Ridge Department of Energy complex are recorded in Part B. Included are sections on biological sciences, energy, engineering, environmental sciences, health and safety, and safeguards. Part C summarizes the various educational activities in which the staff was engaged. Part Dmore » lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

A simulations approach for meta-analysis of genetic association studies based on additive genetic model.

PubMed

John, Majnu; Lencz, Todd; Malhotra, Anil K; Correll, Christoph U; Zhang, Jian-Ping

2018-06-01

Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.

Microscopic saw mark analysis: an empirical approach.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2015-01-01

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

PubMed

Becker, Betsy Jane; Aloe, Ariel M; Duvendack, Maren; Stanley, T D; Valentine, Jeffrey C; Fretheim, Atle; Tugwell, Peter

2017-09-01

To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences. Copyright © 2017 Elsevier Inc. All rights reserved.

Two-dimensional random surface model for asperity-contact in elastohydrodynamic lubrication

NASA Technical Reports Server (NTRS)

Coy, J. J.; Sidik, S. M.

1979-01-01

Relations for the asperity-contact time function during elastohydrodynamic lubrication of a ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces are used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately four to five. This thickness ratio is several times large than reported in the literature where one-dimensional random surface models were used. It is shown that low pass filtering of the statistical records will bring agreement between the present results and those in the literature.

Percolation Analysis as a Tool to Describe the Topology of the Large Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Yess, Capp D.

1997-09-01

Percolation analysis is the study of the properties of clusters. In cosmology, it is the statistics of the size and number of clusters. This thesis presents a refinement of percolation analysis and its application to astronomical data. An overview of the standard model of the universe and the development of large scale structure is presented in order to place the study in historical and scientific context. Then using percolation statistics we, for the first time, demonstrate the universal character of a network pattern in the real space, mass distributions resulting from nonlinear gravitational instability of initial Gaussian fluctuations. We also find that the maximum of the number of clusters statistic in the evolved, nonlinear distributions is determined by the effective slope of the power spectrum. Next, we present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range β = 0.1 to 1.0, where β=Ω0.6/b,/ Ω is the present dimensionless density and b is the linear bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, R≈100h-1 Mpc, percolation analysis reveals a slight 'meatball' topology for the real space, galaxy distribution of the IRAS survey. Finally, we employ a percolation technique developed for pointwise distributions to analyze two-dimensional projections of the three northern and three southern slices in the Las Campanas Redshift Survey and then give consideration to further study of the methodology, errors and application of percolation. We track the growth of the largest cluster as a topological indicator to a depth of 400 h-1 Mpc, and report an unambiguous signal, with high signal-to-noise ratio, indicating a network topology which in two dimensions is indicative of a filamentary distribution. It is hoped that one day percolation analysis can characterize the structure of the universe to a degree that will aid theorists in confidently describing the nature of our world.

A note on statistical analysis of shape through triangulation of landmarks

PubMed Central

Rao, C. Radhakrishna

2000-01-01

In an earlier paper, the author jointly with S. Suryawanshi proposed statistical analysis of shape through triangulation of landmarks on objects. It was observed that the angles of the triangles are invariant to scaling, location, and rotation of objects. No distinction was made between an object and its reflection. The present paper provides the methodology of shape discrimination when reflection is also taken into account and makes suggestions for modifications to be made when some of the landmarks are collinear. PMID:10737780

Orchestrating high-throughput genomic analysis with Bioconductor

PubMed Central

Huber, Wolfgang; Carey, Vincent J.; Gentleman, Robert; Anders, Simon; Carlson, Marc; Carvalho, Benilton S.; Bravo, Hector Corrada; Davis, Sean; Gatto, Laurent; Girke, Thomas; Gottardo, Raphael; Hahne, Florian; Hansen, Kasper D.; Irizarry, Rafael A.; Lawrence, Michael; Love, Michael I.; MacDonald, James; Obenchain, Valerie; Oleś, Andrzej K.; Pagès, Hervé; Reyes, Alejandro; Shannon, Paul; Smyth, Gordon K.; Tenenbaum, Dan; Waldron, Levi; Morgan, Martin

2015-01-01

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors. PMID:25633503

Photon counting statistics analysis of biophotons from hands.

PubMed

Jung, Hyun-Hee; Woo, Won-Myung; Yang, Joon-Mo; Choi, Chunho; Lee, Jonghan; Yoon, Gilwon; Yang, Jong S; Soh, Kwang-Sup

2003-05-01

The photon counting statistics of biophotons emitted from hands is studied with a view to test its agreement with the Poisson distribution. The moments of observed probability up to seventh order have been evaluated. The moments of biophoton emission from hands are in good agreement while those of dark counts of photomultiplier tube show large deviations from the theoretical values of Poisson distribution. The present results are consistent with the conventional delta-value analysis of the second moment of probability.

A New Methodology for Systematic Exploitation of Technology Databases.

ERIC Educational Resources Information Center

Bedecarrax, Chantal; Huot, Charles

1994-01-01

Presents the theoretical aspects of a data analysis methodology that can help transform sequential raw data from a database into useful information, using the statistical analysis of patents as an example. Topics discussed include relational analysis and a technology watch approach. (Contains 17 references.) (LRW)

Test 6, Test 7, and Gas Standard Analysis Results

NASA Technical Reports Server (NTRS)

Perez, Horacio, III

2007-01-01

This viewgraph presentation shows results of analyses on odor, toxic off gassing and gas standards. The topics include: 1) Statistical Analysis Definitions; 2) Odor Analysis Results NASA Standard 6001 Test 6; 3) Toxic Off gassing Analysis Results NASA Standard 6001 Test 7; and 4) Gas Standard Results NASA Standard 6001 Test 7;

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1991-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

An issue of literacy on pediatric arterial hypertension

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Romana, Andreia; Simão, Carla

2017-11-01

Arterial hypertension in pediatric age is a public health problem, whose prevalence has increased significantly over time. Pediatric arterial hypertension (PAH) is under-diagnosed in most cases, a highly prevalent disease, appears without notice with multiple consequences on the children's health and future adults. Children caregivers and close family must know the PAH existence, the negative consequences associated with it, the risk factors and, finally, must do prevention. In [12, 13] can be found a statistical data analysis using a simpler questionnaire introduced in [4] under the aim of a preliminary study about PAH caregivers acquaintance. A continuation of such analysis is detailed in [14]. An extension of such questionnaire was built and applied to a distinct population and it was filled online. The statistical approach is partially reproduced in the present work. Some statistical models were estimated using several approaches, namely multivariate analysis (factorial analysis), also adequate methods to analyze the kind of data in study.

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1990-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, Janine Camille; Thompson, David; Pebay, Philippe Pierre

Statistical analysis is typically used to reduce the dimensionality of and infer meaning from data. A key challenge of any statistical analysis package aimed at large-scale, distributed data is to address the orthogonal issues of parallel scalability and numerical stability. Many statistical techniques, e.g., descriptive statistics or principal component analysis, are based on moments and co-moments and, using robust online update formulas, can be computed in an embarrassingly parallel manner, amenable to a map-reduce style implementation. In this paper we focus on contingency tables, through which numerous derived statistics such as joint and marginal probability, point-wise mutual information, information entropy,more » and {chi}{sup 2} independence statistics can be directly obtained. However, contingency tables can become large as data size increases, requiring a correspondingly large amount of communication between processors. This potential increase in communication prevents optimal parallel speedup and is the main difference with moment-based statistics (which we discussed in [1]) where the amount of inter-processor communication is independent of data size. Here we present the design trade-offs which we made to implement the computation of contingency tables in parallel. We also study the parallel speedup and scalability properties of our open source implementation. In particular, we observe optimal speed-up and scalability when the contingency statistics are used in their appropriate context, namely, when the data input is not quasi-diffuse.« less

Statistical and data reporting guidelines for the European Journal of Cardio-Thoracic Surgery and the Interactive CardioVascular and Thoracic Surgery.

PubMed

Hickey, Graeme L; Dunning, Joel; Seifert, Burkhardt; Sodeck, Gottfried; Carr, Matthew J; Burger, Hans Ulrich; Beyersdorf, Friedhelm

2015-08-01

As part of the peer review process for the European Journal of Cardio-Thoracic Surgery (EJCTS) and the Interactive CardioVascular and Thoracic Surgery (ICVTS), a statistician reviews any manuscript that includes a statistical analysis. To facilitate authors considering submitting a manuscript and to make it clearer about the expectations of the statistical reviewers, we present up-to-date guidelines for authors on statistical and data reporting specifically in these journals. The number of statistical methods used in the cardiothoracic literature is vast, as are the ways in which data are presented. Therefore, we narrow the scope of these guidelines to cover the most common applications submitted to the EJCTS and ICVTS, focusing in particular on those that the statistical reviewers most frequently comment on. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

PubMed Central

Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

PubMed

Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

Statistics, Uncertainty, and Transmitted Variation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, Joanne Roth

2014-11-05

The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.

Archival Legacy Investigations of Circumstellar Environments (ALICE): Statistical assessment of point source detections

NASA Astrophysics Data System (ADS)

Choquet, Élodie; Pueyo, Laurent; Soummer, Rémi; Perrin, Marshall D.; Hagan, J. Brendan; Gofas-Salas, Elena; Rajan, Abhijith; Aguilar, Jonathan

2015-09-01

The ALICE program, for Archival Legacy Investigation of Circumstellar Environment, is currently conducting a virtual survey of about 400 stars, by re-analyzing the HST-NICMOS coronagraphic archive with advanced post-processing techniques. We present here the strategy that we adopted to identify detections and potential candidates for follow-up observations, and we give a preliminary overview of our detections. We present a statistical analysis conducted to evaluate the confidence level on these detection and the completeness of our candidate search.

Statistical Measurements of Contact Conditions of 478 Transport-airplane Landings During Routine Daytime Operations

NASA Technical Reports Server (NTRS)

Silsby, Norman S

1955-01-01

Statistical measurements of contact conditions have been obtained, by means of a special photographic technique, of 478 landings of present-day transport airplanes made during routine daylight operations in clear air at the Washington National Airport. From the measurements, sinking speeds, rolling velocities, bank angles, and horizontal speeds at the instant before contact have been evaluated and a limited statistical analysis of the results has been made and is reported in this report.

Permutation entropy and statistical complexity analysis of turbulence in laboratory plasmas and the solar wind.

PubMed

Weck, P J; Schaffner, D A; Brown, M R; Wicks, R T

2015-02-01

The Bandt-Pompe permutation entropy and the Jensen-Shannon statistical complexity are used to analyze fluctuating time series of three different turbulent plasmas: the magnetohydrodynamic (MHD) turbulence in the plasma wind tunnel of the Swarthmore Spheromak Experiment (SSX), drift-wave turbulence of ion saturation current fluctuations in the edge of the Large Plasma Device (LAPD), and fully developed turbulent magnetic fluctuations of the solar wind taken from the Wind spacecraft. The entropy and complexity values are presented as coordinates on the CH plane for comparison among the different plasma environments and other fluctuation models. The solar wind is found to have the highest permutation entropy and lowest statistical complexity of the three data sets analyzed. Both laboratory data sets have larger values of statistical complexity, suggesting that these systems have fewer degrees of freedom in their fluctuations, with SSX magnetic fluctuations having slightly less complexity than the LAPD edge I(sat). The CH plane coordinates are compared to the shape and distribution of a spectral decomposition of the wave forms. These results suggest that fully developed turbulence (solar wind) occupies the lower-right region of the CH plane, and that other plasma systems considered to be turbulent have less permutation entropy and more statistical complexity. This paper presents use of this statistical analysis tool on solar wind plasma, as well as on an MHD turbulent experimental plasma.

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Visualization of time series statistical data by shape analysis (GDP ratio changes among Asia countries)

NASA Astrophysics Data System (ADS)

Shirota, Yukari; Hashimoto, Takako; Fitri Sari, Riri

2018-03-01

It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called “statistical shape analysis” or “geometry driven statistics” on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

Urological research in sub-Saharan Africa: a retrospective cohort study of abstracts presented at the Nigerian Association of Urological Surgeons conferences.

PubMed

Bello, Jibril Oyekunle

2013-11-14

Nigeria is one of the top three countries in Africa in terms of science research output and Nigerian urologists' biomedical research output contributes to this. Each year, urologists in Nigeria gather to present their recent research at the conference of the Nigerian Association of Urological Surgeons (NAUS). These abstracts are not thoroughly vetted as are full length manuscripts published in peer reviewed journals but the information they disseminate may affect clinical practice of attendees. This study aims to describe the characteristics of abstracts presented at the annual conferences of NAUS, the quality of the abstracts as determined by the subsequent publication of full length manuscripts in peer-review indexed journals and the factors that influence such successful publication. Abstracts presented at the 2007 to 2010 NAUS conferences were identified through conference abstracts books. Using a strict search protocol, publication in peer-reviewed journals was determined. The abstracts characteristics were analyzed and their quality judged by subsequent successful publishing of full length manuscripts. Statistical analysis was performed using SPSS 16.0 software to determine factors predictive of successful publication. Only 75 abstracts were presented at the NAUS 2007 to 2010 conferences; a quarter (24%) of the presented abstracts was subsequently published as full length manuscripts. Median time to publication was 15 months (range 2-40 months). Manuscripts whose result data were analyzed with 'beyond basic' statistics of frequencies and averages were more likely to be published than those with basic or no statistics. Quality of the abstracts and thus subsequent publication success is influenced by the use of 'beyond basic' statistics in analysis of the result data presented. There is a need for improvement in the quality of urological research from Nigeria.

Statistical analysis for understanding and predicting battery degradations in real-life electric vehicle use

NASA Astrophysics Data System (ADS)

Barré, Anthony; Suard, Frédéric; Gérard, Mathias; Montaru, Maxime; Riu, Delphine

2014-01-01

This paper describes the statistical analysis of recorded data parameters of electrical battery ageing during electric vehicle use. These data permit traditional battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on battery ageing phenomena. Predictive battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and battery ageing global observations, and also allow accurate battery ageing diagnosis through predictive models.

Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

Statistical Analysis of Sport Movement Observations: the Case of Orienteering

NASA Astrophysics Data System (ADS)

Amouzandeh, K.; Karimipour, F.

2017-09-01

Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope) and non-spatial movement attributes (e.g. speed and heart rate) of athletes. As the case study, an example dataset of movement observations acquired during the "orienteering" sport is presented and statistically analyzed.

A methodological analysis of chaplaincy research: 2000-2009.

PubMed

Galek, Kathleen; Flannelly, Kevin J; Jankowski, Katherine R B; Handzo, George F

2011-01-01

The present article presents a comprehensive review and analysis of quantitative research conducted in the United States on chaplaincy and closely related topics published between 2000 and 2009. A combined search strategy identified 49 quantitative studies in 13 journals. The analysis focuses on the methodological sophistication of the studies, compared to earlier research on chaplaincy and pastoral care. Cross-sectional surveys of convenience samples still dominate the field, but sample sizes have increased somewhat over the past three decades. Reporting of the validity and reliability of measures continues to be low, although reporting of response rates has improved. Improvements in the use of inferential statistics and statistical controls were also observed, compared to previous research. The authors conclude that more experimental research is needed on chaplaincy, along with an increased use of hypothesis testing, regardless of the research designs that are used.

Assessment of statistical methods used in library-based approaches to microbial source tracking.

PubMed

Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D

2003-12-01

Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.

Quantile regression for the statistical analysis of immunological data with many non-detects.

PubMed

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

How Does One Assess the Accuracy of Academic Success Predictors? ROC Analysis Applied to University Entrance Factors

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

This article attempts to present a novel application of a method of measuring accuracy for academic success predictors that could be used as a standard. This procedure is known as the receiver operating characteristic (ROC) curve, which comes from statistical decision techniques. The statistical prediction techniques provide predictor models and…

Measuring the Effects of Peer Learning on Students' Academic Achievement in First-Year Business Statistics

ERIC Educational Resources Information Center

Dancer, Diane; Morrison, Kellie; Tarr, Garth

2015-01-01

Peer-assisted study session (PASS) programs have been shown to positively affect students' grades in a majority of studies. This study extends that analysis in two ways: controlling for ability and other factors, with focus on international students, and by presenting results for PASS in business statistics. Ordinary least squares, random effects…

Type Ia Supernova Intrinsic Magnitude Dispersion and the Fitting of Cosmological Parameters

NASA Astrophysics Data System (ADS)

Kim, A. G.

2011-02-01

I present an analysis for fitting cosmological parameters from a Hubble diagram of a standard candle with unknown intrinsic magnitude dispersion. The dispersion is determined from the data, simultaneously with the cosmological parameters. This contrasts with the strategies used to date. The advantages of the presented analysis are that it is done in a single fit (it is not iterative), it provides a statistically founded and unbiased estimate of the intrinsic dispersion, and its cosmological-parameter uncertainties account for the intrinsic-dispersion uncertainty. Applied to Type Ia supernovae, my strategy provides a statistical measure to test for subtypes and assess the significance of any magnitude corrections applied to the calibrated candle. Parameter bias and differences between likelihood distributions produced by the presented and currently used fitters are negligibly small for existing and projected supernova data sets.

Response of SiC{sub f}/Si{sub 3}N{sub 4} composites under static and cyclic loading -- An experimental and statistical analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahfuz, H.; Maniruzzaman, M.; Vaidya, U.

1997-04-01

Monotonic tensile and fatigue response of continuous silicon carbide fiber reinforced silicon nitride (SiC{sub f}/Si{sub 3}N{sub 4}) composites has been investigated. The monotonic tensile tests have been performed at room and elevated temperatures. Fatigue tests have been conducted at room temperature (RT), at a stress ratio, R = 0.1 and a frequency of 5 Hz. It is observed during the monotonic tests that the composites retain only 30% of its room temperature strength at 1,600 C suggesting a substantial chemical degradation of the matrix at that temperature. The softening of the matrix at elevated temperature also causes reduction in tensilemore » modulus, and the total reduction in modulus is around 45%. Fatigue data have been generated at three load levels and the fatigue strength of the composite has been found to be considerably high; about 75% of its ultimate room temperature strength. Extensive statistical analysis has been performed to understand the degree of scatter in the fatigue as well as in the static test data. Weibull shape factors and characteristic values have been determined for each set of tests and their relationship with the response of the composites has been discussed. A statistical fatigue life prediction method developed from the Weibull distribution is also presented. Maximum Likelihood Estimator with censoring techniques and data pooling schemes has been employed to determine the distribution parameters for the statistical analysis. These parameters have been used to generate the S-N diagram with desired level of reliability. Details of the statistical analysis and the discussion of the static and fatigue behavior of the composites are presented in this paper.« less

ENVIRONMENTAL ECONOMICS FOR WATERSHED RESTORATION

EPA Science Inventory

This book overviews non-market valuation, input-output analysis, cost-benefit analysis, and presents case studies from the Mid Atlantic Highland region, with all but the bare minimum econometrics, statistics, and math excluded or relegated to an appendix. It is a non-market valu...

Protein Multiplexed Immunoassay Analysis with R.

PubMed

Breen, Edmond J

2017-01-01

Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex ® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex ® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex ® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.

Biomedical applications of aerospace technology

NASA Technical Reports Server (NTRS)

Castles, T. R.

1971-01-01

Aerospace technology transfer to biomedical research problems is discussed, including transfer innovations and potential applications. Statistical analysis of the transfer activities and impact is also presented.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Statistical significance of trace evidence matches using independent physicochemical measurements

NASA Astrophysics Data System (ADS)

Almirall, Jose R.; Cole, Michael; Furton, Kenneth G.; Gettinby, George

1997-02-01

A statistical approach to the significance of glass evidence is proposed using independent physicochemical measurements and chemometrics. Traditional interpretation of the significance of trace evidence matches or exclusions relies on qualitative descriptors such as 'indistinguishable from,' 'consistent with,' 'similar to' etc. By performing physical and chemical measurements with are independent of one another, the significance of object exclusions or matches can be evaluated statistically. One of the problems with this approach is that the human brain is excellent at recognizing and classifying patterns and shapes but performs less well when that object is represented by a numerical list of attributes. Chemometrics can be employed to group similar objects using clustering algorithms and provide statistical significance in a quantitative manner. This approach is enhanced when population databases exist or can be created and the data in question can be evaluated given these databases. Since the selection of the variables used and their pre-processing can greatly influence the outcome, several different methods could be employed in order to obtain a more complete picture of the information contained in the data. Presently, we report on the analysis of glass samples using refractive index measurements and the quantitative analysis of the concentrations of the metals: Mg, Al, Ca, Fe, Mn, Ba, Sr, Ti and Zr. The extension of this general approach to fiber and paint comparisons also is discussed. This statistical approach should not replace the current interpretative approaches to trace evidence matches or exclusions but rather yields an additional quantitative measure. The lack of sufficient general population databases containing the needed physicochemical measurements and the potential for confusion arising from statistical analysis currently hamper this approach and ways of overcoming these obstacles are presented.

New software for statistical analysis of Cambridge Structural Database data

PubMed Central

Sykes, Richard A.; McCabe, Patrick; Allen, Frank H.; Battle, Gary M.; Bruno, Ian J.; Wood, Peter A.

2011-01-01

A collection of new software tools is presented for the analysis of geometrical, chemical and crystallographic data from the Cambridge Structural Database (CSD). This software supersedes the program Vista. The new functionality is integrated into the program Mercury in order to provide statistical, charting and plotting options alongside three-dimensional structural visualization and analysis. The integration also permits immediate access to other information about specific CSD entries through the Mercury framework, a common requirement in CSD data analyses. In addition, the new software includes a range of more advanced features focused towards structural analysis such as principal components analysis, cone-angle correction in hydrogen-bond analyses and the ability to deal with topological symmetry that may be exhibited in molecular search fragments. PMID:22477784

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 analysis of polarization-inhomogeneous Fourier spectra of laser radiation scattered by human skin in the tasks of differentiation of benign and malignant formations

NASA Astrophysics Data System (ADS)

Ushenko, Alexander G.; Dubolazov, Alexander V.; Ushenko, Vladimir A.; Novakovskaya, Olga Y.

2016-07-01

The optical model of formation of polarization structure of laser radiation scattered by polycrystalline networks of human skin in Fourier plane was elaborated. The results of investigation of the values of statistical (statistical moments of the 1st to 4th order) parameters of polarization-inhomogeneous images of skin surface in Fourier plane were presented. The diagnostic criteria of pathological process in human skin and its severity degree differentiation were determined.

Bayesian networks and statistical analysis application to analyze the diagnostic test accuracy

NASA Astrophysics Data System (ADS)

Orzechowski, P.; Makal, Jaroslaw; Onisko, A.

2005-02-01

The computer aided BPH diagnosis system based on Bayesian network is described in the paper. First result are compared to a given statistical method. Different statistical methods are used successfully in medicine for years. However, the undoubted advantages of probabilistic methods make them useful in application in newly created systems which are frequent in medicine, but do not have full and competent knowledge. The article presents advantages of the computer aided BPH diagnosis system in clinical practice for urologists.

From fields to objects: A review of geographic boundary analysis

NASA Astrophysics Data System (ADS)

Jacquez, G. M.; Maruca, S.; Fortin, M.-J.

Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique for defining objects - geographic boundaries - on spatial fields, and for evaluating the statistical significance of characteristics of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes (variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic boundary analysis is clearly a valuable addition to the spatial statistical toolbox. This paper presents the philosophy of, and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques, with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the implementation of these methods within geographic boundary analysis software: GEM.

Statistical analysis and interpolation of compositional data in materials science.

PubMed

Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M

2015-02-09

Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.

Technology, Data Bases and System Analysis for Space-to-Ground Optical Communications

NASA Technical Reports Server (NTRS)

Lesh, James

1995-01-01

Optical communications is becoming an ever-increasingly important option for designers of space-to- ground communications links, whether it be for government or commercial applications. In this paper the technology being developed by NASA for use in space-to-ground optical communications is presented. Next, a program which is collecting a long term data base of atmospheric visibility statistics for optical propagation through the atmosphere will be described. Finally, a methodology for utilizing the statistics of the atmospheric data base in the analysis of space-to-ground links will be presented. This methodology takes into account the effects of station availability, is useful when comparing optical communications with microwave systems, and provides a rationale establishing the recommended link margin.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

Wavelet analysis of birefringence images of myocardium tissue

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Yu.; Ushenko, Yu. O.; Kushnerik, L.; Soltys, I. V.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Introduction of statistical information in a syntactic analyzer for document image recognition

NASA Astrophysics Data System (ADS)

Maroneze, André O.; Coüasnon, Bertrand; Lemaitre, Aurélie

2011-01-01

This paper presents an improvement to document layout analysis systems, offering a possible solution to Sayre's paradox (which states that an element "must be recognized before it can be segmented; and it must be segmented before it can be recognized"). This improvement, based on stochastic parsing, allows integration of statistical information, obtained from recognizers, during syntactic layout analysis. We present how this fusion of numeric and symbolic information in a feedback loop can be applied to syntactic methods to improve document description expressiveness. To limit combinatorial explosion during exploration of solutions, we devised an operator that allows optional activation of the stochastic parsing mechanism. Our evaluation on 1250 handwritten business letters shows this method allows the improvement of global recognition scores.

A statistical method for measuring activation of gene regulatory networks.

PubMed

Esteves, Gustavo H; Reis, Luiz F L

2018-06-13

Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation. The real probability distribution for the test statistic is evaluated by a permutation based study. To illustrate the functionality of the proposed methodology, we also present a simple example based on a small hypothetical network and the activation measuring of two KEGG networks, both based on gene expression data collected from gastric and esophageal samples. The two KEGG networks were also analyzed for a public database, available through NCBI-GEO, presented as Supplementary Material. This method was implemented in an R package that is available at the BioConductor project website under the name maigesPack.

Using SPSS to Analyze Book Collection Data.

ERIC Educational Resources Information Center

Townley, Charles T.

1981-01-01

Describes and illustrates Statistical Package for the Social Sciences (SPSS) procedures appropriate for book collection data analysis. Several different procedures for univariate, bivariate, and multivariate analysis are discussed, and applications of procedures for book collection studies are presented. Included are 24 tables illustrating output…

Neural network approach in multichannel auditory event-related potential analysis.

PubMed

Wu, F Y; Slater, J D; Ramsay, R E

1994-04-01

Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

Statistical functions and relevant correlation coefficients of clearness index

NASA Astrophysics Data System (ADS)

Pavanello, Diego; Zaaiman, Willem; Colli, Alessandra; Heiser, John; Smith, Scott

2015-08-01

This article presents a statistical analysis of the sky conditions, during years from 2010 to 2012, for three different locations: the Joint Research Centre site in Ispra (Italy, European Solar Test Installation - ESTI laboratories), the site of National Renewable Energy Laboratory in Golden (Colorado, USA) and the site of Brookhaven National Laboratories in Upton (New York, USA). The key parameter is the clearness index kT, a dimensionless expression of the global irradiance impinging upon a horizontal surface at a given instant of time. In the first part, the sky conditions are characterized using daily averages, giving a general overview of the three sites. In the second part the analysis is performed using data sets with a short-term resolution of 1 sample per minute, demonstrating remarkable properties of the statistical distributions of the clearness index, reinforced by a proof using fuzzy logic methods. Successively some time-dependent correlations between different meteorological variables are presented in terms of Pearson and Spearman correlation coefficients, and introducing a new one.

Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results

NASA Technical Reports Server (NTRS)

Meuer, Hans-Werner; Simon, Horst D.; Strohmeier, Erich; Lasinski, T. A. (Technical Monitor)

1994-01-01

In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.

Navigation and Dispersion Analysis of the First Orion Exploration Mission

NASA Technical Reports Server (NTRS)

Zanetti, Renato; D'Souza, Christopher

2015-01-01

This paper seeks to present the Orion EM-1 Linear Covariance Analysis for the DRO mission. The delta V statistics for each maneuver are presented. Included in the memo are several sensitivity analyses: variation in the time of OTC-1 (the first outbound correction maneuver), variation in the accuracy of the trans-Lunar injection, and variation in the length of the optical navigation passes.

AIDS Education for Tanzanian Youth: A Mediation Analysis

ERIC Educational Resources Information Center

Stigler, Melissa H.; Kugler, K. C.; Komro, K. A.; Leshabari, M. T.; Klepp, K. I.

2006-01-01

Mediation analysis is a statistical technique that can be used to identify mechanisms by which intervention programs achieve their effects. This paper presents the results of a mediation analysis of Ngao, an acquired immunodeficiency syndrome (AIDS) education program that was implemented with school children in Grades 6 and 7 in Tanzania in the…

Web 2.0 in the Professional LIS Literature: An Exploratory Analysis

ERIC Educational Resources Information Center

Aharony, Noa

2011-01-01

This paper presents a statistical descriptive analysis and a thorough content analysis of descriptors and journal titles extracted from the Library and Information Science Abstracts (LISA) database, focusing on the subject of Web 2.0 and its main applications: blog, wiki, social network and tags.The primary research questions include: whether the…

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.

Software for Data Analysis with Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Roy, H. Scott

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

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.

Analysis models for the estimation of oceanic fields

NASA Technical Reports Server (NTRS)

Carter, E. F.; Robinson, A. R.

1987-01-01

A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariate datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic time series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.

Flexible statistical modelling detects clinical functional magnetic resonance imaging activation in partially compliant subjects.

PubMed

Waites, Anthony B; Mannfolk, Peter; Shaw, Marnie E; Olsrud, Johan; Jackson, Graeme D

2007-02-01

Clinical functional magnetic resonance imaging (fMRI) occasionally fails to detect significant activation, often due to variability in task performance. The present study seeks to test whether a more flexible statistical analysis can better detect activation, by accounting for variance associated with variable compliance to the task over time. Experimental results and simulated data both confirm that even at 80% compliance to the task, such a flexible model outperforms standard statistical analysis when assessed using the extent of activation (experimental data), goodness of fit (experimental data), and area under the operator characteristic curve (simulated data). Furthermore, retrospective examination of 14 clinical fMRI examinations reveals that in patients where the standard statistical approach yields activation, there is a measurable gain in model performance in adopting the flexible statistical model, with little or no penalty in lost sensitivity. This indicates that a flexible model should be considered, particularly for clinical patients who may have difficulty complying fully with the study task.

Statistics: The Shape of the Data. Used Numbers: Real Data in the Classroom. Grades 4-6.

ERIC Educational Resources Information Center

Russell, Susan Jo; Corwin, Rebecca B.

A unit of study that introduces collecting, representing, describing, and interpreting data is presented. Suitable for students in grades 4 through 6, it provides a foundation for further work in statistics and data analysis. The investigations may extend from one to four class sessions and are grouped into three parts: "Introduction to Data…

Log Normal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of Alpha Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2008-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log normal distribution function (J Nucl Med 47, 6 (2006) 1049-1058) with the aid of an autoradiographic approach. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analyses of these data. Methods The measured distributions of alpha particle tracks per cell were subjected to statistical tests with Poisson (P), log normal (LN), and Poisson – log normal (P – LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL 210Po-citrate. When cells were exposed to 67 kBq/mL, the P – LN distribution function gave a better fit, however, the underlying activity distribution remained log normal. Conclusions The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:16741316

A statistical study of EMIC waves observed by Cluster: 1. Wave properties

NASA Astrophysics Data System (ADS)

Allen, R. C.; Zhang, J.-C.; Kistler, L. M.; Spence, H. E.; Lin, R.-L.; Klecker, B.; Dunlop, M. W.; André, M.; Jordanova, V. K.

2015-07-01

Electromagnetic ion cyclotron (EMIC) waves are an important mechanism for particle energization and losses inside the magnetosphere. In order to better understand the effects of these waves on particle dynamics, detailed information about the occurrence rate, wave power, ellipticity, normal angle, energy propagation angle distributions, and local plasma parameters are required. Previous statistical studies have used in situ observations to investigate the distribution of these parameters in the magnetic local time versus L-shell (MLT-L) frame within a limited magnetic latitude (MLAT) range. In this study, we present a statistical analysis of EMIC wave properties using 10 years (2001-2010) of data from Cluster, totaling 25,431 min of wave activity. Due to the polar orbit of Cluster, we are able to investigate EMIC waves at all MLATs and MLTs. This allows us to further investigate the MLAT dependence of various wave properties inside different MLT sectors and further explore the effects of Shabansky orbits on EMIC wave generation and propagation. The statistical analysis is presented in two papers. This paper focuses on the wave occurrence distribution as well as the distribution of wave properties. The companion paper focuses on local plasma parameters during wave observations as well as wave generation proxies.

An introduction to Bayesian statistics in health psychology.

PubMed

Depaoli, Sarah; Rus, Holly M; Clifton, James P; van de Schoot, Rens; Tiemensma, Jitske

2017-09-01

The aim of the current article is to provide a brief introduction to Bayesian statistics within the field of health psychology. Bayesian methods are increasing in prevalence in applied fields, and they have been shown in simulation research to improve the estimation accuracy of structural equation models, latent growth curve (and mixture) models, and hierarchical linear models. Likewise, Bayesian methods can be used with small sample sizes since they do not rely on large sample theory. In this article, we discuss several important components of Bayesian statistics as they relate to health-based inquiries. We discuss the incorporation and impact of prior knowledge into the estimation process and the different components of the analysis that should be reported in an article. We present an example implementing Bayesian estimation in the context of blood pressure changes after participants experienced an acute stressor. We conclude with final thoughts on the implementation of Bayesian statistics in health psychology, including suggestions for reviewing Bayesian manuscripts and grant proposals. We have also included an extensive amount of online supplementary material to complement the content presented here, including Bayesian examples using many different software programmes and an extensive sensitivity analysis examining the impact of priors.

Statistical analysis of the electric energy production from photovoltaic conversion using mobile and fixed constructions

NASA Astrophysics Data System (ADS)

Bugała, Artur; Bednarek, Karol; Kasprzyk, Leszek; Tomczewski, Andrzej

2017-10-01

The paper presents the most representative - from the three-year measurement time period - characteristics of daily and monthly electricity production from a photovoltaic conversion using modules installed in a fixed and 2-axis tracking construction. Results are presented for selected summer, autumn, spring and winter days. Analyzed measuring stand is located on the roof of the Faculty of Electrical Engineering Poznan University of Technology building. The basic parameters of the statistical analysis like mean value, standard deviation, skewness, kurtosis, median, range, or coefficient of variation were used. It was found that the asymmetry factor can be useful in the analysis of the daily electricity production from a photovoltaic conversion. In order to determine the repeatability of monthly electricity production, occurring between the summer, and summer and winter months, a non-parametric Mann-Whitney U test was used as a statistical solution. In order to analyze the repeatability of daily peak hours, describing the largest value of the hourly electricity production, a non-parametric Kruskal-Wallis test was applied as an extension of the Mann-Whitney U test. Based on the analysis of the electric energy distribution from a prepared monitoring system it was found that traditional forecasting methods of the electricity production from a photovoltaic conversion, like multiple regression models, should not be the preferred methods of the analysis.

The level crossing rates and associated statistical properties of a random frequency response function

NASA Astrophysics Data System (ADS)

Langley, Robin S.

2018-03-01

This work is concerned with the statistical properties of the frequency response function of the energy of a random system. Earlier studies have considered the statistical distribution of the function at a single frequency, or alternatively the statistics of a band-average of the function. In contrast the present analysis considers the statistical fluctuations over a frequency band, and results are obtained for the mean rate at which the function crosses a specified level (or equivalently, the average number of times the level is crossed within the band). Results are also obtained for the probability of crossing a specified level at least once, the mean rate of occurrence of peaks, and the mean trough-to-peak height. The analysis is based on the assumption that the natural frequencies and mode shapes of the system have statistical properties that are governed by the Gaussian Orthogonal Ensemble (GOE), and the validity of this assumption is demonstrated by comparison with numerical simulations for a random plate. The work has application to the assessment of the performance of dynamic systems that are sensitive to random imperfections.

Trend-surface analysis of morphometric parameters: A case study in southeastern Brazil

NASA Astrophysics Data System (ADS)

Grohmann, Carlos Henrique

2005-10-01

Trend-surface analysis was carried out on data from morphometric parameters isobase and hydraulic gradient. The study area, located in the eastern border of Quadrilátero Ferrífero, southeastern Brazil, presents four main geomorphological units, one characterized by fluvial dissection, two of mountainous relief, with a scarp of hundreds of meters of fall between them, and a flat plateau in the central portion of the fluvially dissected terrains. Morphometric maps were evaluated in GRASS-GIS and statistics were made on R statistical language, using the spatial package. Analysis of variance (ANOVA) was made to test the significance of each surface and the significance of increasing polynomial degree. The best results were achieved with sixth-order surface for isobase and second-order surface for hydraulic gradient. Shape and orientation of residual maps contours for selected trends were compared with structures inferred from several morphometric maps, and a good correlation is present.

Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.

PubMed

Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

2013-10-01

The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the study. This will minimise analytic bias and conforms to current best practice in conducting clinical trials. © 2013 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Statistical analysis of polarization interference images of biological fluids polycrystalline films in the tasks of optical anisotropy weak changes differentiation

NASA Astrophysics Data System (ADS)

Ushenko, Yu. O.; Dubolazov, O. V.; Ushenko, V. O.; Zhytaryuk, V. G.; Prydiy, O. G.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

In this paper, we present the results of a statistical analysis of polarization-interference images of optically thin histological sections of biological tissues and polycrystalline films of biological fluids of human organs. A new analytical parameter is introduced-the local contrast of the interference pattern in the plane of a polarizationinhomogeneous microscopic image of a biological preparation. The coordinate distributions of the given parameter and the sets of statistical moments of the first-fourth order that characterize these distributions are determined. On this basis, the differentiation of degenerative-dystrophic changes in the myocardium and the polycrystalline structure of the synovial fluid of the human knee with different pathologies is realized.

Statistical trends of episiotomy around the world: Comparative systematic review of changing practices.

PubMed

Clesse, Christophe; Lighezzolo-Alnot, Joëlle; De Lavergne, Sylvie; Hamlin, Sandrine; Scheffler, Michèle

2018-06-01

The authors' purpose for this article is to identify, review and interpret all publications about the episiotomy rates worldwide. Based on the criteria from the PRISMA guidelines, twenty databases were scrutinized. All studies which include national statistics related to episiotomy were selected, as well as studies presenting estimated data. Sixty-one papers were selected with publication dates between 1995 and 2016. A static and dynamic analysis of all the results was carried out. The assumption for the decline in the number of episiotomies is discussed and confirmed, recalling that nowadays high rates of episiotomy remain in less industrialized countries and East Asia. Finally, our analysis aims to investigate the potential determinants which influence apparent statistical disparities.

Adverse effects of metallic artifacts on voxel-wise analysis and tract-based spatial statistics in diffusion tensor imaging.

PubMed

Goto, Masami; Abe, Osamu; Hata, Junichi; Fukunaga, Issei; Shimoji, Keigo; Kunimatsu, Akira; Gomi, Tsutomu

2017-02-01

Background Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that reflects the Brownian motion of water molecules constrained within brain tissue. Fractional anisotropy (FA) is one of the most commonly measured DTI parameters, and can be applied to quantitative analysis of white matter as tract-based spatial statistics (TBSS) and voxel-wise analysis. Purpose To show an association between metallic implants and the results of statistical analysis (voxel-wise group comparison and TBSS) for fractional anisotropy (FA) mapping, in DTI of healthy adults. Material and Methods Sixteen healthy volunteers were scanned with 3-Tesla MRI. A magnetic keeper type of dental implant was used as the metallic implant. DTI was acquired three times in each participant: (i) without a magnetic keeper (FAnon1); (ii) with a magnetic keeper (FAimp); and (iii) without a magnetic keeper (FAnon2) as reproducibility of FAnon1. Group comparisons with paired t-test were performed as FAnon1 vs. FAnon2, and as FAnon1 vs. FAimp. Results Regions of significantly reduced and increased local FA values were revealed by voxel-wise group comparison analysis (a P value of less than 0.05, corrected with family-wise error), but not by TBSS. Conclusion Metallic implants existing outside the field of view produce artifacts that affect the statistical analysis (voxel-wise group comparisons) for FA mapping. When statistical analysis for FA mapping is conducted by researchers, it is important to pay attention to any dental implants present in the mouths of the participants.

Analysis of wind bias change with respect to time at Cape Kennedy, Florida, and Vandenberg AFB, California

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1978-01-01

A statistical analysis is presented of the temporal variability of wind vectors at 1 km altitude intervals from 0 to 27 km altitude after applying a digital filter to the original wind profile data sample.

78 FR 59648 - Bureau of Economic Analysis Advisory Committee Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-27

... presented more effectively for current economic analysis and recent statistical developments in national... with disabilities. Requests for foreign language interpretation or other auxiliary aids should be... September 2, 1999. The Committee advises the Director of BEA on matters related to the development and...

Fisher statistics for analysis of diffusion tensor directional information.

PubMed

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. Copyright © 2012 Elsevier B.V. All rights reserved.

Good analytical practice: statistics and handling data in biomedical science. A primer and directions for authors. Part 1: Introduction. Data within and between one or two sets of individuals.

PubMed

Blann, A D; Nation, B R

2008-01-01

The biomedical scientist is bombarded on a daily basis by information, almost all of which refers to the health status of an individual or groups of individuals. This review is the first of a two-part article written to explain some of the issues related to the presentation and analysis of data. The first part focuses on types of data and how to present and analyse data from an individual or from one or two groups of persons. The second part will examine data from three or more sets of persons, what methods are available to allow this analysis (i.e., statistical software packages), and will conclude with a statement on appropriate descriptors of data, their analyses, and presentation for authors considering submission of their data to this journal.

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework

NASA Astrophysics Data System (ADS)

Rubin, D.; Aldering, G.; Barbary, K.; Boone, K.; Chappell, G.; Currie, M.; Deustua, S.; Fagrelius, P.; Fruchter, A.; Hayden, B.; Lidman, C.; Nordin, J.; Perlmutter, S.; Saunders, C.; Sofiatti, C.; Supernova Cosmology Project, The

2015-11-01

While recent supernova (SN) cosmology research has benefited from improved measurements, current analysis approaches are not statistically optimal and will prove insufficient for future surveys. This paper discusses the limitations of current SN cosmological analyses in treating outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations. We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects. We apply the framework to real SN observations and demonstrate smaller statistical and systematic uncertainties. We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way. This analysis was primarily performed blinded, in that the basic framework was first validated on simulated data before transitioning to real data. We also discuss possible extensions of the method.

Preparing for the first meeting with a statistician.

PubMed

De Muth, James E

2008-12-15

Practical statistical issues that should be considered when performing data collection and analysis are reviewed. The meeting with a statistician should take place early in the research development before any study data are collected. The process of statistical analysis involves establishing the research question, formulating a hypothesis, selecting an appropriate test, sampling correctly, collecting data, performing tests, and making decisions. Once the objectives are established, the researcher can determine the characteristics or demographics of the individuals required for the study, how to recruit volunteers, what type of data are needed to answer the research question(s), and the best methods for collecting the required information. There are two general types of statistics: descriptive and inferential. Presenting data in a more palatable format for the reader is called descriptive statistics. Inferential statistics involve making an inference or decision about a population based on results obtained from a sample of that population. In order for the results of a statistical test to be valid, the sample should be representative of the population from which it is drawn. When collecting information about volunteers, researchers should only collect information that is directly related to the study objectives. Important information that a statistician will require first is an understanding of the type of variables involved in the study and which variables can be controlled by researchers and which are beyond their control. Data can be presented in one of four different measurement scales: nominal, ordinal, interval, or ratio. Hypothesis testing involves two mutually exclusive and exhaustive statements related to the research question. Statisticians should not be replaced by computer software, and they should be consulted before any research data are collected. When preparing to meet with a statistician, the pharmacist researcher should be familiar with the steps of statistical analysis and consider several questions related to the study to be conducted.

Compositional data analysis for physical activity, sedentary time and sleep research.

PubMed

Dumuid, Dorothea; Stanford, Tyman E; Martin-Fernández, Josep-Antoni; Pedišić, Željko; Maher, Carol A; Lewis, Lucy K; Hron, Karel; Katzmarzyk, Peter T; Chaput, Jean-Philippe; Fogelholm, Mikael; Hu, Gang; Lambert, Estelle V; Maia, José; Sarmiento, Olga L; Standage, Martyn; Barreira, Tiago V; Broyles, Stephanie T; Tudor-Locke, Catrine; Tremblay, Mark S; Olds, Timothy

2017-01-01

The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children's daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

NASA Technical Reports Server (NTRS)

Tamayo, Tak Chai

1987-01-01

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

Compositional Solution Space Quantification for Probabilistic Software Analysis

NASA Technical Reports Server (NTRS)

Borges, Mateus; Pasareanu, Corina S.; Filieri, Antonio; d'Amorim, Marcelo; Visser, Willem

2014-01-01

Probabilistic software analysis aims at quantifying how likely a target event is to occur during program execution. Current approaches rely on symbolic execution to identify the conditions to reach the target event and try to quantify the fraction of the input domain satisfying these conditions. Precise quantification is usually limited to linear constraints, while only approximate solutions can be provided in general through statistical approaches. However, statistical approaches may fail to converge to an acceptable accuracy within a reasonable time. We present a compositional statistical approach for the efficient quantification of solution spaces for arbitrarily complex constraints over bounded floating-point domains. The approach leverages interval constraint propagation to improve the accuracy of the estimation by focusing the sampling on the regions of the input domain containing the sought solutions. Preliminary experiments show significant improvement on previous approaches both in results accuracy and analysis time.

Rare-Variant Association Analysis: Study Designs and Statistical Tests

PubMed Central

Lee, Seunggeung; Abecasis, Gonçalo R.; Boehnke, Michael; Lin, Xihong

2014-01-01

Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions. PMID:24995866

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

The construction and assessment of a statistical model for the prediction of protein assay data.

PubMed

Pittman, J; Sacks, J; Young, S Stanley

2002-01-01

The focus of this work is the development of a statistical model for a bioinformatics database whose distinctive structure makes model assessment an interesting and challenging problem. The key components of the statistical methodology, including a fast approximation to the singular value decomposition and the use of adaptive spline modeling and tree-based methods, are described, and preliminary results are presented. These results are shown to compare favorably to selected results achieved using comparitive methods. An attempt to determine the predictive ability of the model through the use of cross-validation experiments is discussed. In conclusion a synopsis of the results of these experiments and their implications for the analysis of bioinformatic databases in general is presented.

Primary Student-Teachers' Conceptual Understanding of the Greenhouse Effect: A mixed method study

NASA Astrophysics Data System (ADS)

Ratinen, Ilkka Johannes

2013-04-01

The greenhouse effect is a reasonably complex scientific phenomenon which can be used as a model to examine students' conceptual understanding in science. Primary student-teachers' understanding of global environmental problems, such as climate change and ozone depletion, indicates that they have many misconceptions. The present mixed method study examines Finnish primary student-teachers' understanding of the greenhouse effect based on the results obtained via open-ended and closed-form questionnaires. The open-ended questionnaire considers primary student-teachers' spontaneous ideas about the greenhouse effect depicted by concept maps. The present study also uses statistical analysis to reveal respondents' conceptualization of the greenhouse effect. The concept maps and statistical analysis reveal that the primary student-teachers' factual knowledge and their conceptual understanding of the greenhouse effect are incomplete and even misleading. In the light of the results of the present study, proposals for modifying the instruction of climate change in science, especially in geography, are presented.

The U.S. geological survey rass-statpac system for management and statistical reduction of geochemical data

USGS Publications Warehouse

VanTrump, G.; Miesch, A.T.

1977-01-01

RASS is an acronym for Rock Analysis Storage System and STATPAC, for Statistical Package. The RASS and STATPAC computer programs are integrated into the RASS-STATPAC system for the management and statistical reduction of geochemical data. The system, in its present form, has been in use for more than 9 yr by scores of U.S. Geological Survey geologists, geochemists, and other scientists engaged in a broad range of geologic and geochemical investigations. The principal advantage of the system is the flexibility afforded the user both in data searches and retrievals and in the manner of statistical treatment of data. The statistical programs provide for most types of statistical reduction normally used in geochemistry and petrology, but also contain bridges to other program systems for statistical processing and automatic plotting. ?? 1977.

African Primary Care Research: Quantitative analysis and presentation of results

PubMed Central

Ogunbanjo, Gboyega A.

2014-01-01

Abstract This article is part of a series on Primary Care Research Methods. The article describes types of continuous and categorical data, how to capture data in a spreadsheet, how to use descriptive and inferential statistics and, finally, gives advice on how to present the results in text, figures and tables. The article intends to help Master's level students with writing the data analysis section of their research proposal and presenting their results in their final research report. PMID:26245435

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data.

PubMed

Goulet, Joseph L; Buta, Eugenia; Bathulapalli, Harini; Gueorguieva, Ralitza; Brandt, Cynthia A

2017-03-01

Pain intensity is often measured in clinical and research settings using the 0 to 10 numeric rating scale (NRS). NRS scores are recorded as discrete values, and in some samples they may display a high proportion of zeroes and a right-skewed distribution. Despite this, statistical methods for normally distributed data are frequently used in the analysis of NRS data. We present results from an observational cross-sectional study examining the association of NRS scores with patient characteristics using data collected from a large cohort of 18,935 veterans in Department of Veterans Affairs care diagnosed with a potentially painful musculoskeletal disorder. The mean (variance) NRS pain was 3.0 (7.5), and 34% of patients reported no pain (NRS = 0). We compared the following statistical models for analyzing NRS scores: linear regression, generalized linear models (Poisson and negative binomial), zero-inflated and hurdle models for data with an excess of zeroes, and a cumulative logit model for ordinal data. We examined model fit, interpretability of results, and whether conclusions about the predictor effects changed across models. In this study, models that accommodate zero inflation provided a better fit than the other models. These models should be considered for the analysis of NRS data with a large proportion of zeroes. We examined and analyzed pain data from a large cohort of veterans with musculoskeletal disorders. We found that many reported no current pain on the NRS on the diagnosis date. We present several alternative statistical methods for the analysis of pain intensity data with a large proportion of zeroes. Published by Elsevier Inc.

Results of the NaCo Large Program: probing the occurrence of exoplanets and brown dwarfs at wide orbit

NASA Astrophysics Data System (ADS)

Vigan, A.; Chauvin, G.; Bonavita, M.; Desidera, S.; Bonnefoy, M.; Mesa, D.; Beuzit, J.-L.; Augereau, J.-C.; Biller, B.; Boccaletti, A.; Brugaletta, E.; Buenzli, E.; Carson, J.; Covino, E.; Delorme, P.; Eggenberger, A.; Feldt, M.; Hagelberg, J.; Henning, T.; Lagrange, A.-M.; Lanzafame, A.; Ménard, F.; Messina, S.; Meyer, M.; Montagnier, G.; Mordasini, C.; Mouillet, D.; Moutou, C.; Mugnier, L.; Quanz, S. P.; Reggiani, M.; Ségransan, D.; Thalmann, C.; Waters, R.; Zurlo, A.

2014-01-01

Over the past decade, a growing number of deep imaging surveys have started to provide meaningful constraints on the population of extrasolar giant planets at large orbital separation. Primary targets for these surveys have been carefully selected based on their age, distance and spectral type, and often on their membership to young nearby associations where all stars share common kinematics, photometric and spectroscopic properties. The next step is a wider statistical analysis of the frequency and properties of low mass companions as a function of stellar mass and orbital separation. In late 2009, we initiated a coordinated European Large Program using angular differential imaging in the H band (1.66 μm) with NaCo at the VLT. Our aim is to provide a comprehensive and statistically significant study of the occurrence of extrasolar giant planets and brown dwarfs at large (5-500 AU) orbital separation around ~150 young, nearby stars, a large fraction of which have never been observed at very deep contrast. The survey has now been completed and we present the data analysis and detection limits for the observed sample, for which we reach the planetary-mass domain at separations of >~50 AU on average. We also present the results of the statistical analysis that has been performed over the 75 targets newly observed at high-contrast. We discuss the details of the statistical analysis and the physical constraints that our survey provides for the frequency and formation scenario of planetary mass companions at large separation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zdarek, J.; Pecinka, L.

Leak-before-break (LBB) analysis of WWER type reactors in the Czech and Sloval Republics is summarized in this paper. Legislative bases, required procedures, and validation and verification of procedures are discussed. A list of significant issues identified during the application of LBB analysis is presented. The results of statistical evaluation of crack length characteristics are presented and compared for the WWER 440 Type 230 and 213 reactors and for the WWER 1000 Type 302, 320 and 338 reactors.

Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets

PubMed Central

Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

2013-01-01

Purpose: With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. Methods: A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. Results: The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. Conclusions: The work demonstrates the viability of the design approach and the software tool for analysis of large data sets. PMID:24320426

Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets.

PubMed

Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

2013-11-01

With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. The work demonstrates the viability of the design approach and the software tool for analysis of large data sets.

Improving Recruiting of the 6th Recruiting Brigade Through Statistical Analysis and Efficiency Measures

DTIC Science & Technology

2014-12-01

example of maximizing or minimizing decision variables within a model. Carol Stoker and Stephen Mehay present a comparative analysis of marketing and advertising strategies...strategy development process; documenting various recruiting, marketing , and advertising initiatives in each nation; and examining efforts to

LSD Now: 1973

ERIC Educational Resources Information Center

Chunko, John A.

1973-01-01

LSD NOW is a nationwide, statistical survey and analysis of hallucinogenic drug use by individuals presently in formal educational surroundings. Analysis, concentrating on the extent and rationale related to the use of such drugs, now offers a deeper and more meaningful understanding of a particular facet of the drug culture. This understanding…

Concordance correlation for model performance assessment: An example with reference evapotranspiration

USDA-ARS?s Scientific Manuscript database

Procedures for assessing model performance in agronomy are often arbitrary and not always helpful. An omnibus analysis statistic, concordance correlation, is widely known and used in many other sciences. An illustrative example is presented here. The analysis assumes the exact relationship “observat...

Use of check lists in assessing the statistical content of medical studies.

PubMed Central

Gardner, M J; Machin, D; Campbell, M J

1986-01-01

Two check lists are used routinely in the statistical assessment of manuscripts submitted to the "BMJ." One is for papers of a general nature and the other specifically for reports on clinical trials. Each check list includes questions on the design, conduct, analysis, and presentation of studies, and answers to these contribute to the overall statistical evaluation. Only a small proportion of submitted papers are assessed statistically, and these are selected at the refereeing or editorial stage. Examination of the use of the check lists showed that most papers contained statistical failings, many of which could easily be remedied. It is recommended that the check lists should be used by statistical referees, editorial staff, and authors and also during the design stage of studies. PMID:3082452

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

[Notes on vital statistics for the study of perinatal health].

PubMed

Juárez, Sol Pía

2014-01-01

Vital statistics, published by the National Statistics Institute in Spain, are a highly important source for the study of perinatal health nationwide. However, the process of data collection is not well-known and has implications both for the quality and interpretation of the epidemiological results derived from this source. The aim of this study was to present how the information is collected and some of the associated problems. This study is the result of an analysis of the methodological notes from the National Statistics Institute and first-hand information obtained from hospitals, the Central Civil Registry of Madrid, and the Madrid Institute for Statistics. Greater integration between these institutions is required to improve the quality of birth and stillbirth statistics. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Library and Information Science Research Areas: A Content Analysis of Articles from the Top 10 Journals 2007-8

ERIC Educational Resources Information Center

Aharony, Noa

2012-01-01

The current study seeks to describe and analyze journal research publications in the top 10 Library and Information Science journals from 2007-8. The paper presents a statistical descriptive analysis of authorship patterns (geographical distribution and affiliation) and keywords. Furthermore, it displays a thorough content analysis of keywords and…

Support Provided to the External Tank (ET) Project on the Use of Statistical Analysis for ET Certification Consultation Position Paper

NASA Technical Reports Server (NTRS)

Null, Cynthia H.

2009-01-01

In June 2004, the June Space Flight Leadership Council (SFLC) assigned an action to the NASA Engineering and Safety Center (NESC) and External Tank (ET) project jointly to characterize the available dataset [of defect sizes from dissections of foam], identify resultant limitations to statistical treatment of ET as-built foam as part of the overall thermal protection system (TPS) certification, and report to the Program Requirements Change Board (PRCB) and SFLC in September 2004. The NESC statistics team was formed to assist the ET statistics group in August 2004. The NESC's conclusions are presented in this report.

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Statistical flaws in design and analysis of fertility treatment studies on cryopreservation raise doubts on the conclusions

PubMed Central

van Gelder, P.H.A.J.M.; Nijs, M.

2011-01-01

Decisions about pharmacotherapy are being taken by medical doctors and authorities based on comparative studies on the use of medications. In studies on fertility treatments in particular, the methodological quality is of utmost importance in the application of evidence-based medicine and systematic reviews. Nevertheless, flaws and omissions appear quite regularly in these types of studies. Current study aims to present an overview of some of the typical statistical flaws, illustrated by a number of example studies which have been published in peer reviewed journals. Based on an investigation of eleven studies at random selected on fertility treatments with cryopreservation, it appeared that the methodological quality of these studies often did not fulfil the required statistical criteria. The following statistical flaws were identified: flaws in study design, patient selection, and units of analysis or in the definition of the primary endpoints. Other errors could be found in p-value and power calculations or in critical p-value definitions. Proper interpretation of the results and/or use of these study results in a meta analysis should therefore be conducted with care. PMID:24753877

Statistical flaws in design and analysis of fertility treatment -studies on cryopreservation raise doubts on the conclusions.

PubMed

van Gelder, P H A J M; Nijs, M

2011-01-01

Decisions about pharmacotherapy are being taken by medical doctors and authorities based on comparative studies on the use of medications. In studies on fertility treatments in particular, the methodological quality is of utmost -importance in the application of evidence-based medicine and systematic reviews. Nevertheless, flaws and omissions appear quite regularly in these types of studies. Current study aims to present an overview of some of the typical statistical flaws, illustrated by a number of example studies which have been published in peer reviewed journals. Based on an investigation of eleven studies at random selected on fertility treatments with cryopreservation, it appeared that the methodological quality of these studies often did not fulfil the -required statistical criteria. The following statistical flaws were identified: flaws in study design, patient selection, and units of analysis or in the definition of the primary endpoints. Other errors could be found in p-value and power calculations or in critical p-value definitions. Proper -interpretation of the results and/or use of these study results in a meta analysis should therefore be conducted with care.

Assessment of chamber pressure oscillations in the Shuttle SRB

NASA Technical Reports Server (NTRS)

Mathes, H. B.

1980-01-01

Combustion stability evaluations of the Shuttle solid propellant booster motor are reviewed. Measurement of the amplitude and frequency of low level chamber pressure oscillations which have been detected in motor firings, are discussed and a statistical analysis of the data is presented. Oscillatory data from three recent motor firings are shown and the results are compared with statistical predictions which are based on earlier motor firings.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Sound transmission loss of composite sandwich panels

NASA Astrophysics Data System (ADS)

Zhou, Ran

Light composite sandwich panels are increasingly used in automobiles, ships and aircraft, because of the advantages they offer of high strength-to-weight ratios. However, the acoustical properties of these light and stiff structures can be less desirable than those of equivalent metal panels. These undesirable properties can lead to high interior noise levels. A number of researchers have studied the acoustical properties of honeycomb and foam sandwich panels. Not much work, however, has been carried out on foam-filled honeycomb sandwich panels. In this dissertation, governing equations for the forced vibration of asymmetric sandwich panels are developed. An analytical expression for modal densities of symmetric sandwich panels is derived from a sixth-order governing equation. A boundary element analysis model for the sound transmission loss of symmetric sandwich panels is proposed. Measurements of the modal density, total loss factor, radiation loss factor, and sound transmission loss of foam-filled honeycomb sandwich panels with different configurations and thicknesses are presented. Comparisons between the predicted sound transmission loss values obtained from wave impedance analysis, statistical energy analysis, boundary element analysis, and experimental values are presented. The wave impedance analysis model provides accurate predictions of sound transmission loss for the thin foam-filled honeycomb sandwich panels at frequencies above their first resonance frequencies. The predictions from the statistical energy analysis model are in better agreement with the experimental transmission loss values of the sandwich panels when the measured radiation loss factor values near coincidence are used instead of the theoretical values for single-layer panels. The proposed boundary element analysis model provides more accurate predictions of sound transmission loss for the thick foam-filled honeycomb sandwich panels than either the wave impedance analysis model or the statistical energy analysis model.

Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design.

PubMed

Selvarasu, Suresh; Kim, Do Yun; Karimi, Iftekhar A; Lee, Dong-Yup

2010-10-01

We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in the feed medium can be inferred, potentially leading to an increase in cell viability and productivity, as well as a decrease in toxic waste production. The study demonstrated how the current methodological framework using multivariate statistical analysis techniques can serve as a potential tool for deriving rational medium design strategies. Copyright © 2010 Elsevier B.V. All rights reserved.

Network Meta-Analysis Using R: A Review of Currently Available Automated Packages

PubMed Central

Neupane, Binod; Richer, Danielle; Bonner, Ashley Joel; Kibret, Taddele; Beyene, Joseph

2014-01-01

Network meta-analysis (NMA) – a statistical technique that allows comparison of multiple treatments in the same meta-analysis simultaneously – has become increasingly popular in the medical literature in recent years. The statistical methodology underpinning this technique and software tools for implementing the methods are evolving. Both commercial and freely available statistical software packages have been developed to facilitate the statistical computations using NMA with varying degrees of functionality and ease of use. This paper aims to introduce the reader to three R packages, namely, gemtc, pcnetmeta, and netmeta, which are freely available software tools implemented in R. Each automates the process of performing NMA so that users can perform the analysis with minimal computational effort. We present, compare and contrast the availability and functionality of different important features of NMA in these three packages so that clinical investigators and researchers can determine which R packages to implement depending on their analysis needs. Four summary tables detailing (i) data input and network plotting, (ii) modeling options, (iii) assumption checking and diagnostic testing, and (iv) inference and reporting tools, are provided, along with an analysis of a previously published dataset to illustrate the outputs available from each package. We demonstrate that each of the three packages provides a useful set of tools, and combined provide users with nearly all functionality that might be desired when conducting a NMA. PMID:25541687

Network meta-analysis using R: a review of currently available automated packages.

PubMed

Neupane, Binod; Richer, Danielle; Bonner, Ashley Joel; Kibret, Taddele; Beyene, Joseph

2014-01-01

Network meta-analysis (NMA)--a statistical technique that allows comparison of multiple treatments in the same meta-analysis simultaneously--has become increasingly popular in the medical literature in recent years. The statistical methodology underpinning this technique and software tools for implementing the methods are evolving. Both commercial and freely available statistical software packages have been developed to facilitate the statistical computations using NMA with varying degrees of functionality and ease of use. This paper aims to introduce the reader to three R packages, namely, gemtc, pcnetmeta, and netmeta, which are freely available software tools implemented in R. Each automates the process of performing NMA so that users can perform the analysis with minimal computational effort. We present, compare and contrast the availability and functionality of different important features of NMA in these three packages so that clinical investigators and researchers can determine which R packages to implement depending on their analysis needs. Four summary tables detailing (i) data input and network plotting, (ii) modeling options, (iii) assumption checking and diagnostic testing, and (iv) inference and reporting tools, are provided, along with an analysis of a previously published dataset to illustrate the outputs available from each package. We demonstrate that each of the three packages provides a useful set of tools, and combined provide users with nearly all functionality that might be desired when conducting a NMA.

Statistical analysis tables for truncated or censored samples

NASA Technical Reports Server (NTRS)

Cohen, A. C.; Cooley, C. G.

1971-01-01

Compilation describes characteristics of truncated and censored samples, and presents six illustrations of practical use of tables in computing mean and variance estimates for normal distribution using selected samples.

Application of modified profile analysis to function testing of the motion/no-motion issue in an aircraft ground-handling simulation. [statistical analysis procedure for man machine systems flight simulation

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Steinmetz, G. G.

1979-01-01

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

An overview of data acquisition, signal coding and data analysis techniques for MST radars

NASA Technical Reports Server (NTRS)

Rastogi, P. K.

1986-01-01

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Statistical methods for astronomical data with upper limits. I - Univariate distributions

NASA Technical Reports Server (NTRS)

Feigelson, E. D.; Nelson, P. I.

1985-01-01

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

New Trends in Mathematics Teaching, Volume III.

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Paris (France).

Each of the ten chapters in this volume is intended to present an objective analysis of the trends of some important subtopic in mathematics education and each includes a bibliography for fuller study. The chapters cover primary school mathematics, algebra, geometry, probability and statistics, analysis, logic, applications of mathematics, methods…

DNA Fingerprinting in a Forensic Teaching Experiment

ERIC Educational Resources Information Center

Wagoner, Stacy A.; Carlson, Kimberly A.

2008-01-01

This article presents an experiment designed to provide students, in a classroom laboratory setting, a hands-on demonstration of the steps used in DNA forensic analysis by performing DNA extraction, DNA fingerprinting, and statistical analysis of the data. This experiment demonstrates how DNA fingerprinting is performed and how long it takes. It…

Regression Commonality Analysis: A Technique for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…

Analysis of vector wind change with respect to time for Vandenberg Air Force Base, California

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1978-01-01

A statistical analysis of the temporal variability of wind vectors at 1 km altitude intervals from 0 to 27 km altitude taken from a 10-year data sample of twice-daily rawinsode wind measurements over Vandenberg Air Force Base, California is presented.

Exploration of the Maximum Entropy/Optimal Projection Approach to Control Design Synthesis for Large Space Structures.

DTIC Science & Technology

1985-02-01

Energy Analysis , a branch of dynamic modal analysis developed for analyzing acoustic vibration problems, its present stage of development embodies a...Maximum Entropy Stochastic Modelling and Reduced-Order Design Synthesis is a rigorous new approach to this class of problems. Inspired by Statistical

Analysis of Variance in Statistical Image Processing

NASA Astrophysics Data System (ADS)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Arthrodesis following failed total knee arthroplasty: comprehensive review and meta-analysis of recent literature.

PubMed

Damron, T A; McBeath, A A

1995-04-01

With the increasing duration of follow up on total knee arthroplasties, more revision arthroplasties are being performed. When revision is not advisable, a salvage procedure such as arthrodesis or resection arthroplasty is indicated. This article provides a comprehensive review of the literature regarding arthrodesis following failed total knee arthroplasty. In addition, a statistical meta-analysis of five studies using modern arthrodesis techniques is presented. A statistically significant greater fusion rate with intramedullary nail arthrodesis compared to external fixation is documented. Gram negative and mixed infections are found to be significant risk factors for failure of arthrodesis.

Statistical analysis of experimental data for mathematical modeling of physical processes in the atmosphere

NASA Astrophysics Data System (ADS)

Karpushin, P. A.; Popov, Yu B.; Popova, A. I.; Popova, K. Yu; Krasnenko, N. P.; Lavrinenko, A. V.

2017-11-01

In this paper, the probabilities of faultless operation of aerologic stations are analyzed, the hypothesis of normality of the empirical data required for using the Kalman filter algorithms is tested, and the spatial correlation functions of distributions of meteorological parameters are determined. The results of a statistical analysis of two-term (0, 12 GMT) radiosonde observations of the temperature and wind velocity components at some preset altitude ranges in the troposphere in 2001-2016 are presented. These data can be used in mathematical modeling of physical processes in the atmosphere.

The data life cycle applied to our own data.

PubMed

Goben, Abigail; Raszewski, Rebecca

2015-01-01

Increased demand for data-driven decision making is driving the need for librarians to be facile with the data life cycle. This case study follows the migration of reference desk statistics from handwritten to digital format. This shift presented two opportunities: first, the availability of a nonsensitive data set to improve the librarians' understanding of data-management and statistical analysis skills, and second, the use of analytics to directly inform staffing decisions and departmental strategic goals. By working through each step of the data life cycle, library faculty explored data gathering, storage, sharing, and analysis questions.

Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

2016-02-01

Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple `fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Attitudes towards schizophrenia on YouTube: A content analysis of Finnish and Greek videos.

PubMed

Athanasopoulou, Christina; Suni, Sanna; Hätönen, Heli; Apostolakis, Ioannis; Lionis, Christos; Välimäki, Maritta

2016-01-01

To investigate attitudes towards schizophrenia and people with schizophrenia presented in YouTube videos. We searched YouTube using the search terms "schizophrenia" and "psychosis" in Finnish and Greek language on April 3rd, 2013. The first 20 videos from each search (N = 80) were retrieved. Deductive content analysis was first applied for coding and data interpretation and it was followed by descriptive statistical analysis. A total of 52 videos were analyzed (65%). The majority of the videos were in the "Music" category (50%, n = 26). Most of the videos (83%, n = 43) tended to present schizophrenia in a negative way, while less than a fifth (17%, n = 9) presented schizophrenia in a positive or neutral way. Specifically, the most common negative attitude towards schizophrenia was dangerousness (29%, n = 15), while the most often identified positive attitude was objective, medically appropriate beliefs (21%, n = 11). All attitudes identified were similarly present in the Finnish and Greek videos, without any statistically significant difference. Negative presentations of schizophrenia are most likely to be accessed when searching YouTube for schizophrenia in Finnish and Greek language. More research is needed to investigate to what extent, if any, YouTube viewers' attitudes are affected by the videos they watch.

Atmospheric Tracer Inverse Modeling Using Markov Chain Monte Carlo (MCMC)

NASA Astrophysics Data System (ADS)

Kasibhatla, P.

2004-12-01

In recent years, there has been an increasing emphasis on the use of Bayesian statistical estimation techniques to characterize the temporal and spatial variability of atmospheric trace gas sources and sinks. The applications have been varied in terms of the particular species of interest, as well as in terms of the spatial and temporal resolution of the estimated fluxes. However, one common characteristic has been the use of relatively simple statistical models for describing the measurement and chemical transport model error statistics and prior source statistics. For example, multivariate normal probability distribution functions (pdfs) are commonly used to model these quantities and inverse source estimates are derived for fixed values of pdf paramaters. While the advantage of this approach is that closed form analytical solutions for the a posteriori pdfs of interest are available, it is worth exploring Bayesian analysis approaches which allow for a more general treatment of error and prior source statistics. Here, we present an application of the Markov Chain Monte Carlo (MCMC) methodology to an atmospheric tracer inversion problem to demonstrate how more gereral statistical models for errors can be incorporated into the analysis in a relatively straightforward manner. The MCMC approach to Bayesian analysis, which has found wide application in a variety of fields, is a statistical simulation approach that involves computing moments of interest of the a posteriori pdf by efficiently sampling this pdf. The specific inverse problem that we focus on is the annual mean CO2 source/sink estimation problem considered by the TransCom3 project. TransCom3 was a collaborative effort involving various modeling groups and followed a common modeling and analysis protocoal. As such, this problem provides a convenient case study to demonstrate the applicability of the MCMC methodology to atmospheric tracer source/sink estimation problems.

Periods of High Intensity Solar Proton Flux

NASA Technical Reports Server (NTRS)

Xapsos, Michael A.; Stauffer, Craig A.; Jordan, Thomas M.; Adams, James H.; Dietrich, William F.

2012-01-01

Analysis is presented for times during a space mission that specified solar proton flux levels are exceeded. This includes both total time and continuous time periods during missions. Results for the solar maximum and solar minimum phases of the solar cycle are presented and compared for a broad range of proton energies and shielding levels. This type of approach is more amenable to reliability analysis for spacecraft systems and instrumentation than standard statistical models.

The Effects of Auditory Tempo Changes on Rates of Stereotypic Behavior in Handicapped Children.

ERIC Educational Resources Information Center

Christopher, R.; Lewis, B.

1984-01-01

Rates of stereotypic behaviors in six severely/profoundly retarded children (eight to 15 years old) were observed during varying presentations of auditory beats produced by a metronome. Visual and statistical analysis of research results suggested a significant reaction to stimulus presentation. However, additional data following…

The problem of extreme events in paired-watershed studies

Treesearch

James W. Hornbeck

1973-01-01

In paired-watershed studies, the occurrence of an extreme event during the after-treatment period presents a problem: the effects of treatment must be determined by using greatly extrapolated regression statistics. Several steps are presented to help insure careful handling of extreme events during analysis and reporting of research results.

The contribution of molecular relaxation in nitrogen to the absorption of sound in the atmosphere

NASA Technical Reports Server (NTRS)

Zuckerwar, A. J.; Meredith, R. W.

1980-01-01

Results and statistical analysis are presented for sound absorption in N2-H2O binary mixtures at room temperature. Experimental procedure, temperature effects, and preliminary results are presented for sound absorption in N2-H2O binary mixtures at elevated temperatures.

Development of the Research Competencies Scale

ERIC Educational Resources Information Center

Swank, Jacqueline M.; Lambie, Glenn W.

2016-01-01

The authors present the development of the Research Competencies Scale (RCS). The purpose of this article is threefold: (a) present a rationale for the RCS, (b) review statistical analysis procedures used in developing the RCS, and (c) offer implications for counselor education, the enhancement of scholar-researchers, and future research.

A LISREL Model for the Analysis of Repeated Measures with a Patterned Covariance Matrix.

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

1998-01-01

Presents a LISREL model for the estimation of the repeated measures analysis of variance (ANOVA) with a patterned covariance matrix. The model is demonstrated for a 5 x 2 (Time x Group) ANOVA in which the data are assumed to be serially correlated. Similarities with the Statistical Analysis System PROC MIXED model are discussed. (SLD)

Universal Recurrence Time Statistics of Characteristic Earthquakes

NASA Astrophysics Data System (ADS)

Goltz, C.; Turcotte, D. L.; Abaimov, S.; Nadeau, R. M.

2006-12-01

Characteristic earthquakes are defined to occur quasi-periodically on major faults. Do recurrence time statistics of such earthquakes follow a particular statistical distribution? If so, which one? The answer is fundamental and has important implications for hazard assessment. The problem cannot be solved by comparing the goodness of statistical fits as the available sequences are too short. The Parkfield sequence of M ≍ 6 earthquakes, one of the most extensive reliable data sets available, has grown to merely seven events with the last earthquake in 2004, for example. Recently, however, advances in seismological monitoring and improved processing methods have unveiled so-called micro-repeaters, micro-earthquakes which recur exactly in the same location on a fault. It seems plausible to regard these earthquakes as a miniature version of the classic characteristic earthquakes. Micro-repeaters are much more frequent than major earthquakes, leading to longer sequences for analysis. Due to their recent discovery, however, available sequences contain less than 20 events at present. In this paper we present results for the analysis of recurrence times for several micro-repeater sequences from Parkfield and adjacent regions. To improve the statistical significance of our findings, we combine several sequences into one by rescaling the individual sets by their respective mean recurrence intervals and Weibull exponents. This novel approach of rescaled combination yields the most extensive data set possible. We find that the resulting statistics can be fitted well by an exponential distribution, confirming the universal applicability of the Weibull distribution to characteristic earthquakes. A similar result is obtained from rescaled combination, however, with regard to the lognormal distribution.

Where statistics and molecular microarray experiments biology meet.

PubMed

Kelmansky, Diana M

2013-01-01

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

Polarization-interference Jones-matrix mapping of biological crystal networks

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Dubolazov, O. V.; Pidkamin, L. Y.; Sidor, M. I.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of Jones-matrix mapping with the help of reference wave. It was provided experimentally measured coordinate distributions of modulus of Jones-matrix elements of polycrystalline film of bile. It was defined the values and ranges of changing of statistic moments, which characterize such distributions. The second part presents the data of statistic analysis of the distributions of matrix elements of polycrystalline film of urine of donors and patients with albuminuria. It was defined the objective criteria of differentiation of albuminuria.

WASP (Write a Scientific Paper) using Excel - 2: Pivot tables.

PubMed

Grech, Victor

2018-02-01

Data analysis at the descriptive stage and the eventual presentation of results requires the tabulation and summarisation of data. This exercise should always precede inferential statistics. Pivot tables and pivot charts are one of Excel's most powerful and underutilised features, with tabulation functions that immensely facilitate descriptive statistics. Pivot tables permit users to dynamically summarise and cross-tabulate data, create tables in several dimensions, offer a range of summary statistics and can be modified interactively with instant outputs. Large and detailed datasets are thereby easily manipulated making pivot tables arguably the best way to explore, summarise and present data from many different angles. This second paper in the WASP series in Early Human Development provides pointers for pivot table manipulation in Excel™. Copyright © 2018 Elsevier B.V. All rights reserved.

Cloud encounter statistics in the 28.5-43.5 KFT altitude region from four years of GASP observations

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastrom, G. D.; Davis, R. E.; Holdeman, J. D.

1983-01-01

The results of an analysis of cloud encounter measurements taken at aircraft flight altitudes as part of the Global Atmospheric Sampling Program are summarized. The results can be used in estimating the probability of cloud encounter and in assessing the economic feasibility of laminar flow control aircraft along particular routes. The data presented clearly show the tropical circulation and its seasonal migration; characteristics of the mid-latitude regime, such as the large-scale traveling cyclones in the winter and increased convective activity in the summer, can be isolated in the data. The cloud encounter statistics are shown to be consistent with the mid-latitude cyclone model. A model for TIC (time-in-clouds), a cloud encounter statistic, is presented for several common airline routes.

Point process statistics in atom probe tomography.

PubMed

Philippe, T; Duguay, S; Grancher, G; Blavette, D

2013-09-01

We present a review of spatial point processes as statistical models that we have designed for the analysis and treatment of atom probe tomography (APT) data. As a major advantage, these methods do not require sampling. The mean distance to nearest neighbour is an attractive approach to exhibit a non-random atomic distribution. A χ(2) test based on distance distributions to nearest neighbour has been developed to detect deviation from randomness. Best-fit methods based on first nearest neighbour distance (1 NN method) and pair correlation function are presented and compared to assess the chemical composition of tiny clusters. Delaunay tessellation for cluster selection has been also illustrated. These statistical tools have been applied to APT experiments on microelectronics materials. Copyright © 2012 Elsevier B.V. All rights reserved.

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

NASA Technical Reports Server (NTRS)

Abbey, Craig K.; Eckstein, Miguel P.

2002-01-01

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Identifiability of PBPK Models with Applications to ...

EPA Pesticide Factsheets

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

A statistical study of EMIC waves observed by Cluster. 1. Wave properties. EMIC Wave Properties

DOE PAGES

Allen, R. C.; Zhang, J. -C.; Kistler, L. M.; ...

2015-07-23

Electromagnetic ion cyclotron (EMIC) waves are an important mechanism for particle energization and losses inside the magnetosphere. In order to better understand the effects of these waves on particle dynamics, detailed information about the occurrence rate, wave power, ellipticity, normal angle, energy propagation angle distributions, and local plasma parameters are required. Previous statistical studies have used in situ observations to investigate the distribution of these parameters in the magnetic local time versus L-shell (MLT-L) frame within a limited magnetic latitude (MLAT) range. In our study, we present a statistical analysis of EMIC wave properties using 10 years (2001–2010) of datamore » from Cluster, totaling 25,431 min of wave activity. Due to the polar orbit of Cluster, we are able to investigate EMIC waves at all MLATs and MLTs. This allows us to further investigate the MLAT dependence of various wave properties inside different MLT sectors and further explore the effects of Shabansky orbits on EMIC wave generation and propagation. Thus, the statistical analysis is presented in two papers. OUr paper focuses on the wave occurrence distribution as well as the distribution of wave properties. The companion paper focuses on local plasma parameters during wave observations as well as wave generation proxies.« less

Using Data Analysis to Explore Class Enrollment.

ERIC Educational Resources Information Center

Davis, Gretchen

1990-01-01

Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)

Immunohistochemical evaluation of inducible nitric oxide synthase in the epithelial lining of odontogenic cysts: A qualitative and quantitative analysis

PubMed Central

Akshatha, B K; Karuppiah, Karpagaselvi; Manjunath, G S; Kumarswamy, Jayalakshmi; Papaiah, Lokesh; Rao, Jyothi

2017-01-01

Introduction: The three common odontogenic cysts include radicular cysts (RCs), dentigerous cysts (DCs), and odontogenic keratocysts (OKCs). Among these 3 cysts, OKC is recently been classified as benign keratocystic odontogenic tumor attributing to its aggressive behavior, recurrence rate, and malignant potential. The present study involved qualitative and quantitative analysis of inducible nitric oxide synthase (iNOS) expression in epithelial lining of RCs, DCs, and OKCs, compare iNOS expression in epithelial linings of all the 3 cysts and determined overexpression of iNOS in OKCs which might contribute to its aggressive behavior and malignant potential. Aims: The present study is to investigate the role of iNOS in the pathogenesis of OKCs, DCs, and RCs by evaluating the iNOS expression in the epithelial lining of these cysts. Subjects and Methods: Analysis of iNOS expression in epithelial lining cells of 20 RCs, 20 DCs, and 20 OKCs using immunohistochemistry done. Statistical Analysis Used: The percentage of positive cells and intensity of stain was assessed and compared among all the 3 cysts using contingency coefficient. Kappa statistics for the two observers were computed for finding interobserver agreement. Results: The percentage of iNOS-positive cells was found to be remarkably high in OKCs (12/20) –57.1% as compared to RCs (6/20) – 28.6% and DCs (3/20) – 14.3%. The interobserver agreement for iNOS-positive percentage cells was arrived with kappa values with OKCs → Statistically significant (P > 0.000), RCs → statistically significant (P > 0.001) with no significant values for DCs. No statistical difference exists among 3 study samples in regard to the intensity of staining with iNOS. Conclusions: Increased iNOS expression in OKCs may contribute to bone resorption and accumulation of wild-type p53, hence, making OKCs more aggressive. PMID:29391711

The effect of normalization of Partial Directed Coherence on the statistical assessment of connectivity patterns: a simulation study.

PubMed

Toppi, J; Petti, M; Vecchiato, G; Cincotti, F; Salinari, S; Mattia, D; Babiloni, F; Astolfi, L

2013-01-01

Partial Directed Coherence (PDC) is a spectral multivariate estimator for effective connectivity, relying on the concept of Granger causality. Even if its original definition derived directly from information theory, two modifies were introduced in order to provide better physiological interpretations of the estimated networks: i) normalization of the estimator according to rows, ii) squared transformation. In the present paper we investigated the effect of PDC normalization on the performances achieved by applying the statistical validation process on investigated connectivity patterns under different conditions of Signal to Noise ratio (SNR) and amount of data available for the analysis. Results of the statistical analysis revealed an effect of PDC normalization only on the percentages of type I and type II errors occurred by using Shuffling procedure for the assessment of connectivity patterns. No effects of the PDC formulation resulted on the performances achieved during the validation process executed instead by means of Asymptotic Statistic approach. Moreover, the percentages of both false positives and false negatives committed by Asymptotic Statistic are always lower than those achieved by Shuffling procedure for each type of normalization.

Conducting Simulation Studies in the R Programming Environment.

PubMed

Hallgren, Kevin A

2013-10-12

Simulation studies allow researchers to answer specific questions about data analysis, statistical power, and best-practices for obtaining accurate results in empirical research. Despite the benefits that simulation research can provide, many researchers are unfamiliar with available tools for conducting their own simulation studies. The use of simulation studies need not be restricted to researchers with advanced skills in statistics and computer programming, and such methods can be implemented by researchers with a variety of abilities and interests. The present paper provides an introduction to methods used for running simulation studies using the R statistical programming environment and is written for individuals with minimal experience running simulation studies or using R. The paper describes the rationale and benefits of using simulations and introduces R functions relevant for many simulation studies. Three examples illustrate different applications for simulation studies, including (a) the use of simulations to answer a novel question about statistical analysis, (b) the use of simulations to estimate statistical power, and (c) the use of simulations to obtain confidence intervals of parameter estimates through bootstrapping. Results and fully annotated syntax from these examples are provided.

Potential errors and misuse of statistics in studies on leakage in endodontics.

PubMed

Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

2013-04-01

To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

Comment on “Two statistics for evaluating parameter identifiability and error reduction” by John Doherty and Randall J. Hunt

USGS Publications Warehouse

Hill, Mary C.

2010-01-01

Doherty and Hunt (2009) present important ideas for first-order-second moment sensitivity analysis, but five issues are discussed in this comment. First, considering the composite-scaled sensitivity (CSS) jointly with parameter correlation coefficients (PCC) in a CSS/PCC analysis addresses the difficulties with CSS mentioned in the introduction. Second, their new parameter identifiability statistic actually is likely to do a poor job of parameter identifiability in common situations. The statistic instead performs the very useful role of showing how model parameters are included in the estimated singular value decomposition (SVD) parameters. Its close relation to CSS is shown. Third, the idea from p. 125 that a suitable truncation point for SVD parameters can be identified using the prediction variance is challenged using results from Moore and Doherty (2005). Fourth, the relative error reduction statistic of Doherty and Hunt is shown to belong to an emerging set of statistics here named perturbed calculated variance statistics. Finally, the perturbed calculated variance statistics OPR and PPR mentioned on p. 121 are shown to explicitly include the parameter null-space component of uncertainty. Indeed, OPR and PPR results that account for null-space uncertainty have appeared in the literature since 2000.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Statistical properties of the radiation from SASE FEL operating in the linear regime

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-02-01

The paper presents comprehensive analysis of statistical properties of the radiation from self amplified spontaneous emission (SASE) free electron laser operating in linear mode. The investigation has been performed in a one-dimensional approximation, assuming the electron pulse length to be much larger than a coherence length of the radiation. The following statistical properties of the SASE FEL radiation have been studied: field correlations, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and photoelectric counting statistics of SASE FEL radiation. It is shown that the radiation from SASE FEL operating in linear regime possesses all the features corresponding to completely chaotic polarized radiation.

Testing statistical isotropy in cosmic microwave background polarization maps

NASA Astrophysics Data System (ADS)

Rath, Pranati K.; Samal, Pramoda Kumar; Panda, Srikanta; Mishra, Debesh D.; Aluri, Pavan K.

2018-04-01

We apply our symmetry based Power tensor technique to test conformity of PLANCK Polarization maps with statistical isotropy. On a wide range of angular scales (l = 40 - 150), our preliminary analysis detects many statistically anisotropic multipoles in foreground cleaned full sky PLANCK polarization maps viz., COMMANDER and NILC. We also study the effect of residual foregrounds that may still be present in the Galactic plane using both common UPB77 polarization mask, as well as the individual component separation method specific polarization masks. However, some of the statistically anisotropic modes still persist, albeit significantly in NILC map. We further probed the data for any coherent alignments across multipoles in several bins from the chosen multipole range.

Wisconsin's timberland plantations, 1983.

Treesearch

Sue M. Roussopoulos; Earl C. Leatherberry

1992-01-01

In 1983 the fourth Wisconsin forest inventory found 14.8 million timberland acres of which 622.3 thousand acres (4%) were classified as plantations. This bulletin presents analysis and statistics of area, volume, growth, and mortality.

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

Application of the Statistical ICA Technique in the DANCE Data Analysis

NASA Astrophysics Data System (ADS)

Baramsai, Bayarbadrakh; Jandel, M.; Bredeweg, T. A.; Rusev, G.; Walker, C. L.; Couture, A.; Mosby, S.; Ullmann, J. L.; Dance Collaboration

2015-10-01

The Detector for Advanced Neutron Capture Experiments (DANCE) at the Los Alamos Neutron Science Center is used to improve our understanding of the neutron capture reaction. DANCE is a highly efficient 4 π γ-ray detector array consisting of 160 BaF2 crystals which make it an ideal tool for neutron capture experiments. The (n, γ) reaction Q-value equals to the sum energy of all γ-rays emitted in the de-excitation cascades from the excited capture state to the ground state. The total γ-ray energy is used to identify reactions on different isotopes as well as the background. However, it's challenging to identify contribution in the Esum spectra from different isotopes with the similar Q-values. Recently we have tested the applicability of modern statistical methods such as Independent Component Analysis (ICA) to identify and separate different (n, γ) reaction yields on different isotopes that are present in the target material. ICA is a recently developed computational tool for separating multidimensional data into statistically independent additive subcomponents. In this conference talk, we present some results of the application of ICA algorithms and its modification for the DANCE experimental data analysis. This research is supported by the U. S. Department of Energy, Office of Science, Nuclear Physics under the Early Career Award No. LANL20135009.

Development of a Probabilistic Component Mode Synthesis Method for the Analysis of Non-Deterministic Substructures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1995-01-01

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature, researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. This paper presents a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apte, A; Veeraraghavan, H; Oh, J

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features andmore » (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.« less

Implementation of the medical research curriculum in graduate medical school.

PubMed

Park, Kwi Hwa; Kim, Tae-Hee; Chung, Wook-Jin

2011-06-01

The purpose of this study was to analyze the effect of the medical research curriculum on the students' satisfaction and the research self-efficacy. The curriculum was implemented to 79 graduate medical school students who entered in 2007 and 2008. This curriculum is implemented through 3 years consisting of 5 different sub-courses: Research design, Research ethics, Medical statistics, Writing medical paper, and Presentation. The effect of this program was measured with 2 self-administered surveys to students: the course satisfaction survey and the self-efficacy inventories. The Research Self-Efficacy Scale consisted of 18 items from 4 categories: Research design, Research ethics, Data analysis, and Result presentation. The descriptive statistics, paired t-test, and analysis of covariance (ANCOVA) were implemented. The average point of satisfaction of the course was 2.74 out of 4, which told us that students generally satisfied with the course. The frequencies of tutoring for research course were 2 or 3 times on average and each session of tutorial lasted 1.5 to 2 hours. The research self-efficacy in three categories (Research design, Research ethics, and Result presentation) increased significantly (p<0.1). The self-efficacy of the male students was higher than females' one. The self-efficacy was not significantly different by the experience of research paper writing at undergraduate level. The curriculum showed positive results in cultivating research self-efficacy of students. There is a need for improvement of the class of Statistical analysis as students reported that it was difficult.

Space Shuttle booster thrust imbalance analysis

NASA Technical Reports Server (NTRS)

Bailey, W. R.; Blackwell, D. L.

1985-01-01

An analysis of the Shuttle SRM thrust imbalance during the steady-state and tailoff portions of the boost phase of flight are presented. Results from flights STS-1 through STS-13 are included. A statistical analysis of the observed thrust imbalance data is presented. A 3 sigma thrust imbalance history versus time was generated from the observed data and is compared to the vehicle design requirements. The effect on Shuttle thrust imbalance from the use of replacement SRM segments is predicted. Comparisons of observed thrust imbalances with respect to predicted imbalances are presented for the two space shuttle flights which used replacement aft segments (STS-9 and STS-13).

Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

NASA Astrophysics Data System (ADS)

Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

2018-03-01

This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

Fully Bayesian inference for structural MRI: application to segmentation and statistical analysis of T2-hypointensities.

PubMed

Schmidt, Paul; Schmid, Volker J; Gaser, Christian; Buck, Dorothea; Bührlen, Susanne; Förschler, Annette; Mühlau, Mark

2013-01-01

Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: [Formula: see text]; range, [Formula: see text]). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data.

Anima: Modular Workflow System for Comprehensive Image Data Analysis

PubMed Central

Rantanen, Ville; Valori, Miko; Hautaniemi, Sampsa

2014-01-01

Modern microscopes produce vast amounts of image data, and computational methods are needed to analyze and interpret these data. Furthermore, a single image analysis project may require tens or hundreds of analysis steps starting from data import and pre-processing to segmentation and statistical analysis; and ending with visualization and reporting. To manage such large-scale image data analysis projects, we present here a modular workflow system called Anima. Anima is designed for comprehensive and efficient image data analysis development, and it contains several features that are crucial in high-throughput image data analysis: programing language independence, batch processing, easily customized data processing, interoperability with other software via application programing interfaces, and advanced multivariate statistical analysis. The utility of Anima is shown with two case studies focusing on testing different algorithms developed in different imaging platforms and an automated prediction of alive/dead C. elegans worms by integrating several analysis environments. Anima is a fully open source and available with documentation at www.anduril.org/anima. PMID:25126541

Surface flaw reliability analysis of ceramic components with the SCARE finite element postprocessor program

NASA Technical Reports Server (NTRS)

Gyekenyesi, John P.; Nemeth, Noel N.

1987-01-01

The SCARE (Structural Ceramics Analysis and Reliability Evaluation) computer program on statistical fast fracture reliability analysis with quadratic elements for volume distributed imperfections is enhanced to include the use of linear finite elements and the capability of designing against concurrent surface flaw induced ceramic component failure. The SCARE code is presently coupled as a postprocessor to the MSC/NASTRAN general purpose, finite element analysis program. The improved version now includes the Weibull and Batdorf statistical failure theories for both surface and volume flaw based reliability analysis. The program uses the two-parameter Weibull fracture strength cumulative failure probability distribution model with the principle of independent action for poly-axial stress states, and Batdorf's shear-sensitive as well as shear-insensitive statistical theories. The shear-sensitive surface crack configurations include the Griffith crack and Griffith notch geometries, using the total critical coplanar strain energy release rate criterion to predict mixed-mode fracture. Weibull material parameters based on both surface and volume flaw induced fracture can also be calculated from modulus of rupture bar tests, using the least squares method with known specimen geometry and grouped fracture data. The statistical fast fracture theories for surface flaw induced failure, along with selected input and output formats and options, are summarized. An example problem to demonstrate various features of the program is included.

Structural Blockage: A Cross-national Study of Economic Dependency, State Efficacy, and Underdevelopment.

ERIC Educational Resources Information Center

Delacroix, Jacques; Ragin, Charles C.

1981-01-01

Presents a statistical analysis of dependency of developing nations on more highly developed and industrialized nations and relates this dependency to various degrees of economic development. The analysis is based on the structural blockage argument (one of several dependency arguments contained in many versions of dependency theory). Emphasizes…

Effects of Instructional Design with Mental Model Analysis on Learning.

ERIC Educational Resources Information Center

Hong, Eunsook

This paper presents a model for systematic instructional design that includes mental model analysis together with the procedures used in developing computer-based instructional materials in the area of statistical hypothesis testing. The instructional design model is based on the premise that the objective for learning is to achieve expert-like…

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

Indiana's timber resource, 1986: an analysis.

Treesearch

John S. Jr. Spencer; Neal P. Kingsley; Robert W. Mayer

1990-01-01

The third inventory of Indiana's timber resource shows that area of timberland increased from 3.9 to 4.3 million acres between 1967 and 1986, and growing-stock volume gained from 3.7 to 5.2 billion cubic feet. Presented are analysis and statistics on forest area and timber volume, growth, mortality, removals, and projections.

Missouri's forest resource, 1989: an analysis.

Treesearch

John S. Jr. Spencer; Sue M. Roussopoulos; Robert A. Messengale

1992-01-01

In 1989 the fourth Missouri forest inventory found 14.0 million acres of forest land, of which 13.4 million acres (96%) is timberland. Growing-stock volume increased from 6.5 to 9.0 billion cubic feet between 1972 and 1989. Analysis and statistics on forest area, timber volume, growth, removals, mortality, and projections are presented.

Using Business Analysis Software in a Business Intelligence Course

ERIC Educational Resources Information Center

Elizondo, Juan; Parzinger, Monica J.; Welch, Orion J.

2011-01-01

This paper presents an example of a project used in an undergraduate business intelligence class which integrates concepts from statistics, marketing, and information systems disciplines. SAS Enterprise Miner software is used as the foundation for predictive analysis and data mining. The course culminates with a competition and the project is used…

Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

ERIC Educational Resources Information Center

Young, Cristobal; Holsteen, Katherine

2017-01-01

Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

Vocational Preparation for Women: A Critical Analysis.

ERIC Educational Resources Information Center

Steiger, JoAnn

In this analysis of vocational preparation for women material is presented to substantiate the claim that women are joining the labor force in increasing numbers and their career opportunities are expanding, but that the educational system has failed to respond. Statistical data is cited showing that women have traditionally been employed in just…

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

PubMed Central

2011-01-01

Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim. PMID:21473747

Application of Multivariate Statistical Analysis to Biomarkers in Se-Turkey Crude Oils

NASA Astrophysics Data System (ADS)

Gürgey, K.; Canbolat, S.

2017-11-01

Twenty-four crude oil samples were collected from the 24 oil fields distributed in different districts of SE-Turkey. API and Sulphur content (%), Stable Carbon Isotope, Gas Chromatography (GC), and Gas Chromatography-Mass Spectrometry (GC-MS) data were used to construct a geochemical data matrix. The aim of this study is to examine the genetic grouping or correlations in the crude oil samples, hence the number of source rocks present in the SE-Turkey. To achieve these aims, two of the multivariate statistical analysis techniques (Principle Component Analysis [PCA] and Cluster Analysis were applied to data matrix of 24 samples and 8 source specific biomarker variables/parameters. The results showed that there are 3 genetically different oil groups: Batman-Nusaybin Oils, Adıyaman-Kozluk Oils and Diyarbakir Oils, in addition to a one mixed group. These groupings imply that at least, three different source rocks are present in South-Eastern (SE) Turkey. Grouping of the crude oil samples appears to be consistent with the geographic locations of the oils fields, subsurface stratigraphy as well as geology of the area.

Statistical analysis of dynamic fibrils observed from NST/BBSO observations

NASA Astrophysics Data System (ADS)

Gopalan Priya, Thambaje; Su, Jiang-Tao; Chen, Jie; Deng, Yuan-Yong; Prasad Choudhury, Debi

2018-02-01

We present the results obtained from the analysis of dynamic fibrils in NOAA active region (AR) 12132, using high resolution Hα observations from the New Solar Telescope operating at Big Bear Solar Observatory. The dynamic fibrils are seen to be moving up and down, and most of these dynamic fibrils are periodic and have a jet-like appearance. We found from our observations that the fibrils follow almost perfect parabolic paths in many cases. A statistical analysis on the properties of the parabolic paths showing an analysis on deceleration, maximum velocity, duration and kinetic energy of these fibrils is presented here. We found the average maximum velocity to be around 15 kms‑1 and mean deceleration to be around 100 ms‑2. The observed deceleration appears to be a fraction of gravity of the Sun and is not compatible with the path of ballistic motion due to gravity of the Sun. We found a positive correlation between deceleration and maximum velocity. This correlation is consistent with simulations done earlier on magnetoacoustic shock waves propagating upward.

Statistical analysis plan for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). A randomized controlled trial

PubMed Central

Damiani, Lucas Petri; Berwanger, Otavio; Paisani, Denise; Laranjeira, Ligia Nasi; Suzumura, Erica Aranha; Amato, Marcelo Britto Passos; Carvalho, Carlos Roberto Ribeiro; Cavalcanti, Alexandre Biasi

2017-01-01

Background The Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) is an international multicenter randomized pragmatic controlled trial with allocation concealment involving 120 intensive care units in Brazil, Argentina, Colombia, Italy, Poland, Portugal, Malaysia, Spain, and Uruguay. The primary objective of ART is to determine whether maximum stepwise alveolar recruitment associated with PEEP titration, adjusted according to the static compliance of the respiratory system (ART strategy), is able to increase 28-day survival in patients with acute respiratory distress syndrome compared to conventional treatment (ARDSNet strategy). Objective To describe the data management process and statistical analysis plan. Methods The statistical analysis plan was designed by the trial executive committee and reviewed and approved by the trial steering committee. We provide an overview of the trial design with a special focus on describing the primary (28-day survival) and secondary outcomes. We describe our data management process, data monitoring committee, interim analyses, and sample size calculation. We describe our planned statistical analyses for primary and secondary outcomes as well as pre-specified subgroup analyses. We also provide details for presenting results, including mock tables for baseline characteristics, adherence to the protocol and effect on clinical outcomes. Conclusion According to best trial practice, we report our statistical analysis plan and data management plan prior to locking the database and beginning analyses. We anticipate that this document will prevent analysis bias and enhance the utility of the reported results. Trial registration ClinicalTrials.gov number, NCT01374022. PMID:28977255

Improved Diagnostic Accuracy of SPECT Through Statistical Analysis and the Detection of Hot Spots at the Primary Sensorimotor Area for the Diagnosis of Alzheimer Disease in a Community-Based Study: "The Osaki-Tajiri Project".

PubMed

Kaneta, Tomohiro; Nakatsuka, Masahiro; Nakamura, Kei; Seki, Takashi; Yamaguchi, Satoshi; Tsuboi, Masahiro; Meguro, Kenichi

2016-01-01

SPECT is an important diagnostic tool for dementia. Recently, statistical analysis of SPECT has been commonly used for dementia research. In this study, we evaluated the accuracy of visual SPECT evaluation and/or statistical analysis for the diagnosis (Dx) of Alzheimer disease (AD) and other forms of dementia in our community-based study "The Osaki-Tajiri Project." Eighty-nine consecutive outpatients with dementia were enrolled and underwent brain perfusion SPECT with 99mTc-ECD. Diagnostic accuracy of SPECT was tested using 3 methods: visual inspection (SPECT Dx), automated diagnostic tool using statistical analysis with easy Z-score imaging system (eZIS Dx), and visual inspection plus eZIS (integrated Dx). Integrated Dx showed the highest sensitivity, specificity, and accuracy, whereas eZIS was the second most accurate method. We also observed that a higher than expected rate of SPECT images indicated false-negative cases of AD. Among these, 50% showed hypofrontality and were diagnosed as frontotemporal lobar degeneration. These cases typically showed regional "hot spots" in the primary sensorimotor cortex (ie, a sensorimotor hot spot sign), which we determined were associated with AD rather than frontotemporal lobar degeneration. We concluded that the diagnostic abilities were improved by the integrated use of visual assessment and statistical analysis. In addition, the detection of a sensorimotor hot spot sign was useful to detect AD when hypofrontality is present and improved the ability to properly diagnose AD.

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS.

PubMed

Wiedermann, Wolfgang; Li, Xintong

2018-04-16

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.

Mass detection, localization and estimation for wind turbine blades based on statistical pattern recognition

NASA Astrophysics Data System (ADS)

Colone, L.; Hovgaard, M. K.; Glavind, L.; Brincker, R.

2018-07-01

A method for mass change detection on wind turbine blades using natural frequencies is presented. The approach is based on two statistical tests. The first test decides if there is a significant mass change and the second test is a statistical group classification based on Linear Discriminant Analysis. The frequencies are identified by means of Operational Modal Analysis using natural excitation. Based on the assumption of Gaussianity of the frequencies, a multi-class statistical model is developed by combining finite element model sensitivities in 10 classes of change location on the blade, the smallest area being 1/5 of the span. The method is experimentally validated for a full scale wind turbine blade in a test setup and loaded by natural wind. Mass change from natural causes was imitated with sand bags and the algorithm was observed to perform well with an experimental detection rate of 1, localization rate of 0.88 and mass estimation rate of 0.72.

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

PubMed

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

PubMed Central

Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.

2016-01-01

Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095

Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans.

PubMed

Ghodrati, Masoud; Ghodousi, Mahrad; Yoonessi, Ali

2016-01-01

Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP) in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs' power within theta frequency band (~3-7 Hz). This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception.

Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans

PubMed Central

Ghodrati, Masoud; Ghodousi, Mahrad; Yoonessi, Ali

2016-01-01

Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP) in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs' power within theta frequency band (~3–7 Hz). This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception. PMID:28018197

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

AGR-1 Thermocouple Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeff Einerson

2012-05-01

This report documents an effort to analyze measured and simulated data obtained in the Advanced Gas Reactor (AGR) fuel irradiation test program conducted in the INL's Advanced Test Reactor (ATR) to support the Next Generation Nuclear Plant (NGNP) R&D program. The work follows up on a previous study (Pham and Einerson, 2010), in which statistical analysis methods were applied for AGR-1 thermocouple data qualification. The present work exercises the idea that, while recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, results of the numerical simulations can be used in combination with the statistical analysis methods tomore » further improve qualification of measured data. Additionally, the combined analysis of measured and simulation data can generate insights about simulation model uncertainty that can be useful for model improvement. This report also describes an experimental control procedure to maintain fuel target temperature in the future AGR tests using regression relationships that include simulation results. The report is organized into four chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program, AGR-1 test configuration and test procedure, overview of AGR-1 measured data, and overview of physics and thermal simulation, including modeling assumptions and uncertainties. A brief summary of statistical analysis methods developed in (Pham and Einerson 2010) for AGR-1 measured data qualification within NGNP Data Management and Analysis System (NDMAS) is also included for completeness. Chapters 2-3 describe and discuss cases, in which the combined use of experimental and simulation data is realized. A set of issues associated with measurement and modeling uncertainties resulted from the combined analysis are identified. This includes demonstration that such a combined analysis led to important insights for reducing uncertainty in presentation of AGR-1 measured data (Chapter 2) and interpretation of simulation results (Chapter 3). The statistics-based simulation-aided experimental control procedure described for the future AGR tests is developed and demonstrated in Chapter 4. The procedure for controlling the target fuel temperature (capsule peak or average) is based on regression functions of thermocouple readings and other relevant parameters and accounting for possible changes in both physical and thermal conditions and in instrument performance.« less

Models of dyadic social interaction.

PubMed Central

Griffin, Dale; Gonzalez, Richard

2003-01-01

We discuss the logic of research designs for dyadic interaction and present statistical models with parameters that are tied to psychologically relevant constructs. Building on Karl Pearson's classic nineteenth-century statistical analysis of within-organism similarity, we describe several approaches to indexing dyadic interdependence and provide graphical methods for visualizing dyadic data. We also describe several statistical and conceptual solutions to the 'levels of analytic' problem in analysing dyadic data. These analytic strategies allow the researcher to examine and measure psychological questions of interdependence and social influence. We provide illustrative data from casually interacting and romantic dyads. PMID:12689382

Twenty-five years of maximum-entropy principle

NASA Astrophysics Data System (ADS)

Kapur, J. N.

1983-04-01

The strengths and weaknesses of the maximum entropy principle (MEP) are examined and some challenging problems that remain outstanding at the end of the first quarter century of the principle are discussed. The original formalism of the MEP is presented and its relationship to statistical mechanics is set forth. The use of MEP for characterizing statistical distributions, in statistical inference, nonlinear spectral analysis, transportation models, population density models, models for brand-switching in marketing and vote-switching in elections is discussed. Its application to finance, insurance, image reconstruction, pattern recognition, operations research and engineering, biology and medicine, and nonparametric density estimation is considered.

Estimation of elastic moduli of graphene monolayer in lattice statics approach at nonzero temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zubko, I. Yu., E-mail: zoubko@list.ru; Kochurov, V. I.

2015-10-27

For the aim of the crystal temperature control the computational-statistical approach to studying thermo-mechanical properties for finite sized crystals is presented. The approach is based on the combination of the high-performance computational techniques and statistical analysis of the crystal response on external thermo-mechanical actions for specimens with the statistically small amount of atoms (for instance, nanoparticles). The heat motion of atoms is imitated in the statics approach by including the independent degrees of freedom for atoms connected with their oscillations. We obtained that under heating, graphene material response is nonsymmetric.

An evaluation of intraoperative and postoperative outcomes of torsional mode versus longitudinal ultrasound mode phacoemulsification: a Meta-analysis.

PubMed

Leon, Pia; Umari, Ingrid; Mangogna, Alessandro; Zanei, Andrea; Tognetto, Daniele

2016-01-01

To evaluate and compare the intraoperative parameters and postoperative outcomes of torsional mode and longitudinal mode of phacoemulsification. Pertinent studies were identified by a computerized MEDLINE search from January 2002 to September 2013. The Meta-analysis is composed of two parts. In the first part the intraoperative parameters were considered: ultrasound time (UST) and cumulative dissipated energy (CDE). The intraoperative values were also distinctly considered for two categories (moderate and hard cataract group) depending on the nuclear opacity grade. In the second part of the study the postoperative outcomes as the best corrected visual acuity (BCVA) and the endothelial cell loss (ECL) were taken in consideration. The UST and CDE values proved statistically significant in support of torsional mode for both moderate and hard cataract group. The analysis of BCVA did not present statistically significant difference between the two surgical modalities. The ECL count was statistically significant in support of torsional mode (P<0.001). The Meta-analysis shows the superiority of the torsional mode for intraoperative parameters (UST, CDE) and postoperative ECL outcomes.

An evaluation of intraoperative and postoperative outcomes of torsional mode versus longitudinal ultrasound mode phacoemulsification: a Meta-analysis

PubMed Central

Leon, Pia; Umari, Ingrid; Mangogna, Alessandro; Zanei, Andrea; Tognetto, Daniele

2016-01-01

AIM To evaluate and compare the intraoperative parameters and postoperative outcomes of torsional mode and longitudinal mode of phacoemulsification. METHODS Pertinent studies were identified by a computerized MEDLINE search from January 2002 to September 2013. The Meta-analysis is composed of two parts. In the first part the intraoperative parameters were considered: ultrasound time (UST) and cumulative dissipated energy (CDE). The intraoperative values were also distinctly considered for two categories (moderate and hard cataract group) depending on the nuclear opacity grade. In the second part of the study the postoperative outcomes as the best corrected visual acuity (BCVA) and the endothelial cell loss (ECL) were taken in consideration. RESULTS The UST and CDE values proved statistically significant in support of torsional mode for both moderate and hard cataract group. The analysis of BCVA did not present statistically significant difference between the two surgical modalities. The ECL count was statistically significant in support of torsional mode (P<0.001). CONCLUSION The Meta-analysis shows the superiority of the torsional mode for intraoperative parameters (UST, CDE) and postoperative ECL outcomes. PMID:27366694

Statistical analysis of tiny SXR flares observed by SphinX

NASA Astrophysics Data System (ADS)

Gryciuk, Magdalena; Siarkowski, Marek; Sylwester, Janusz; Kepa, Anna; Gburek, Szymon; Mrozek, Tomasz; Podgórski, Piotr

2015-08-01

The Solar Photometer in X-rays (SphinX) was designed to observe soft X-ray solar emission in the energy range between ~1 keV and 15 keV with the resolution better than 0.5 keV. The instrument operated from February until November 2009 aboard CORONAS-Photon satellite, during the phase of exceptionally low minimum of solar activity. Here we use SphinX data for analysis of micro-flares and brightenings. Despite a very low activity more than a thousand small X-ray events have been recognized by semi-automatic inspection of SphinX light curves. A catalogue of temporal and physical characteristics of these events is shown and discussed and results of the statistical analysis of the catalogue data are presented.

Mathematics and Statistics Research Department progress report, period ending June 30, 1982

DOE Office of Scientific and Technical Information (OSTI.GOV)

Denson, M.V.; Funderlic, R.E.; Gosslee, D.G.

1982-08-01

This report is the twenty-fifth in the series of progress reports of the Mathematics and Statistics Research Department of the Computer Sciences Division, Union Carbide Corporation Nuclear Division (UCC-ND). Part A records research progress in analysis of large data sets, biometrics research, computational statistics, materials science applications, moving boundary problems, numerical linear algebra, and risk analysis. Collaboration and consulting with others throughout the UCC-ND complex are recorded in Part B. Included are sections on biology, chemistry, energy, engineering, environmental sciences, health and safety, materials science, safeguards, surveys, and the waste storage program. Part C summarizes the various educational activities inmore » which the staff was engaged. Part D lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

Structure-Specific Statistical Mapping of White Matter Tracts

PubMed Central

Yushkevich, Paul A.; Zhang, Hui; Simon, Tony; Gee, James C.

2008-01-01

We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome. PMID:18407524

Detection of reflecting surfaces by a statistical model

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Chee-Hung H.

2009-02-01

Remote sensing is widely used assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, current research on automated feature extraction is ignorant of contextual information. As a result, the fidelity of populating attributes corresponding to interesting features and objects cannot be satisfied. In this paper, we present an exploration on meaningful object extraction integrating reflecting surfaces. Detection of specular reflecting surfaces can be useful in target identification and then can be applied to environmental monitoring, disaster prediction and analysis, military, and counter-terrorism. Our method is based on a statistical model to capture the statistical properties of specular reflecting surfaces. And then the reflecting surfaces are detected through cluster analysis.

Geomatic Methods for the Analysis of Data in the Earth Sciences: Lecture Notes in Earth Sciences, Vol. 95

NASA Astrophysics Data System (ADS)

Pavlis, Nikolaos K.

Geomatics is a trendy term that has been used in recent years to describe academic departments that teach and research theories, methods, algorithms, and practices used in processing and analyzing data related to the Earth and other planets. Naming trends aside, geomatics could be considered as the mathematical and statistical “toolbox” that allows Earth scientists to extract information about physically relevant parameters from the available data and accompany such information with some measure of its reliability. This book is an attempt to present the mathematical-statistical methods used in data analysis within various disciplines—geodesy, geophysics, photogrammetry and remote sensing—from a unifying perspective that inverse problem formalism permits. At the same time, it allows us to stretch the relevance of statistical methods in achieving an optimal solution.

The value of a statistical life: a meta-analysis with a mixed effects regression model.

PubMed

Bellavance, François; Dionne, Georges; Lebeau, Martin

2009-03-01

The value of a statistical life (VSL) is a very controversial topic, but one which is essential to the optimization of governmental decisions. We see a great variability in the values obtained from different studies. The source of this variability needs to be understood, in order to offer public decision-makers better guidance in choosing a value and to set clearer guidelines for future research on the topic. This article presents a meta-analysis based on 39 observations obtained from 37 studies (from nine different countries) which all use a hedonic wage method to calculate the VSL. Our meta-analysis is innovative in that it is the first to use the mixed effects regression model [Raudenbush, S.W., 1994. Random effects models. In: Cooper, H., Hedges, L.V. (Eds.), The Handbook of Research Synthesis. Russel Sage Foundation, New York] to analyze studies on the value of a statistical life. We conclude that the variability found in the values studied stems in large part from differences in methodologies.

Comparative Analysis of Academic Grades in Compulsory Secondary Education in Spain Using Statistical Techniques

ERIC Educational Resources Information Center

Veas, Alejandro; Gilar, Raquel; Miñano, Pablo; Castejón, Juan Luis

2017-01-01

The present study, based on the construct comparability approach, performs a comparative analysis of general points average for seven courses, using exploratory factor analysis (EFA) and the Partial Credit model (PCM) with a sample of 1398 student subjects (M = 12.5, SD = 0.67) from 8 schools in the province of Alicante (Spain). EFA confirmed a…

Learning and understanding the Kruskal-Wallis one-way analysis-of-variance-by-ranks test for differences among three or more independent groups.

PubMed

Chan, Y; Walmsley, R P

1997-12-01

When several treatment methods are available for the same problem, many clinicians are faced with the task of deciding which treatment to use. Many clinicians may have conducted informal "mini-experiments" on their own to determine which treatment is best suited for the problem. These results are usually not documented or reported in a formal manner because many clinicians feel that they are "statistically challenged." Another reason may be because clinicians do not feel they have controlled enough test conditions to warrant analysis. In this update, a statistic is described that does not involve complicated statistical assumptions, making it a simple and easy-to-use statistical method. This update examines the use of two statistics and does not deal with other issues that could affect clinical research such as issues affecting credibility. For readers who want a more in-depth examination of this topic, references have been provided. The Kruskal-Wallis one-way analysis-of-variance-by-ranks test (or H test) is used to determine whether three or more independent groups are the same or different on some variable of interest when an ordinal level of data or an interval or ratio level of data is available. A hypothetical example will be presented to explain when and how to use this statistic, how to interpret results using the statistic, the advantages and disadvantages of the statistic, and what to look for in a written report. This hypothetical example will involve the use of ratio data to demonstrate how to choose between using the nonparametric H test and the more powerful parametric F test.

The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity.

PubMed

Christensen, G B; Knight, S; Camp, N J

2009-11-01

We present the "sumLINK" statistic--the sum of multipoint LOD scores for the subset of pedigrees with nominally significant linkage evidence at a given locus--as an alternative to common methods to identify susceptibility loci in the presence of heterogeneity. We also suggest the "sumLOD" statistic (the sum of positive multipoint LOD scores) as a companion to the sumLINK. sumLINK analysis identifies genetic regions of extreme consistency across pedigrees without regard to negative evidence from unlinked or uninformative pedigrees. Significance is determined by an innovative permutation procedure based on genome shuffling that randomizes linkage information across pedigrees. This procedure for generating the empirical null distribution may be useful for other linkage-based statistics as well. Using 500 genome-wide analyses of simulated null data, we show that the genome shuffling procedure results in the correct type 1 error rates for both the sumLINK and sumLOD. The power of the statistics was tested using 100 sets of simulated genome-wide data from the alternative hypothesis from GAW13. Finally, we illustrate the statistics in an analysis of 190 aggressive prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics, where we identified a new susceptibility locus. We propose that the sumLINK and sumLOD are ideal for collaborative projects and meta-analyses, as they do not require any sharing of identifiable data between contributing institutions. Further, loci identified with the sumLINK have good potential for gene localization via statistical recombinant mapping, as, by definition, several linked pedigrees contribute to each peak.

Development of the Ethical and Legal Issues in Counseling Self-Efficacy Scale

ERIC Educational Resources Information Center

Mullen, Patrick R.; Lambie, Glenn W.; Conley, Abigail H.

2014-01-01

The authors present the development of the Ethical and Legal Issues in Counseling Self-Efficacy Scale (ELICSES). The purpose of this article is threefold: (a) present a rationale for the ELICSES, (b) review statistical analysis procedures used to develop the ELICSES, and (c) offer implications for future research and counselor education.

What Time-Series Designs May Have to Offer Educational Researchers.

ERIC Educational Resources Information Center

Kratochwill, Thomas R.; Levin, Joel R.

1978-01-01

The promise of time-series designs for educational research and evaluation is reviewed. Ten time-series designs are presented and discussed in the context of threats to internal and external validity. The advantages and disadvantages of various visual and statistical data-analysis techniques are presented. A bibliography is appended. (Author/RD)

Student Response to Hypermedia in the Lecture Theatre: A Case Study.

ERIC Educational Resources Information Center

Conway, Damian

The Computer Science Department at Monash University (Victoria, Australia) recently began presenting lectures using projection of a hypertext system, HyperLecture, running on a notebook computer as the primary medium. This paper presents a statistical analysis of student reactions to this approach, focusing on the effects, as perceived by the…

A Case-Based Curriculum for Introductory Geology

ERIC Educational Resources Information Center

Goldsmith, David W.

2011-01-01

For the past 5 years I have been teaching my introductory geology class using a case-based method that promotes student engagement and inquiry. This article presents an explanation of how a case-based curriculum differs from a more traditional approach to the material. It also presents a statistical analysis of several years' worth of student…

Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

PubMed Central

Farràs-Permanyer, Laia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel

2015-01-01

In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results. PMID:26300802

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies.

PubMed

Paté-Cornell, M-Elisabeth; Kuypers, Marshall; Smith, Matthew; Keller, Philip

2018-02-01

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system-based for high-consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward-looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high-consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. © 2017 Society for Risk Analysis.

Railroad Classification Yard Technology Manual. Volume III. Freight Car Rollability

DOT National Transportation Integrated Search

1981-07-01

The report presents a survey of rolling resistance research, histograms of rolling resistance from five yards, a statistical regression analysis of causal factors affecting rolling resistance, procedures for constructing a rolling resistance histogra...

A statistical approach to EMI - Theory and experiment

NASA Astrophysics Data System (ADS)

Weiner, Donald; Capraro, Gerard

A probabilistic approach to electromagnetic interference (EMI) is presented. The approach is illustrated by analyzing an experimental circuit in which EMI occurs. Both random and weakly nonlinear effects are accounted for in the analysis.

Evidence-based systematic review of saw palmetto by the Natural Standard Research Collaboration.

PubMed

Ulbricht, Catherine; Basch, Ethan; Bent, Steve; Boon, Heather; Corrado, Michelle; Foppa, Ivo; Hashmi, Sadaf; Hammerness, Paul; Kingsbury, Eileen; Smith, Michael; Szapary, Philippe; Vora, Mamta; Weissner, Wendy

2006-01-01

Here presented is an evidence-based systematic review including written and statistical analysis of scientific literature, expert opinion, folkloric precedent, history, pharmacology, kinetics/dynamics, interactions, adverse effects, toxicology, and dosing.

Differences in game-related statistics of basketball performance by game location for men's winning and losing teams.

PubMed

Gómez, Miguel A; Lorenzo, Alberto; Barakat, Rubén; Ortega, Enrique; Palao, José M

2008-02-01

The aim of the present study was to identify game-related statistics that differentiate winning and losing teams according to game location. The sample included 306 games of the 2004-2005 regular season of the Spanish professional men's league (ACB League). The independent variables were game location (home or away) and game result (win or loss). The game-related statistics registered were free throws (successful and unsuccessful), 2- and 3-point field goals (successful and unsuccessful), offensive and defensive rebounds, blocks, assists, fouls, steals, and turnovers. Descriptive and inferential analyses were done (one-way analysis of variance and discriminate analysis). The multivariate analysis showed that winning teams differ from losing teams in defensive rebounds (SC = .42) and in assists (SC = .38). Similarly, winning teams differ from losing teams when they play at home in defensive rebounds (SC = .40) and in assists (SC = .41). On the other hand, winning teams differ from losing teams when they play away in defensive rebounds (SC = .44), assists (SC = .30), successful 2-point field goals (SC = .31), and unsuccessful 3-point field goals (SC = -.35). Defensive rebounds and assists were the only game-related statistics common to all three analyses.

A Statistical Method for Synthesizing Mediation Analyses Using the Product of Coefficient Approach Across Multiple Trials

PubMed Central

Huang, Shi; MacKinnon, David P.; Perrino, Tatiana; Gallo, Carlos; Cruden, Gracelyn; Brown, C Hendricks

2016-01-01

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: 1) marginal means for mediation path a, the relation of the independent variable to the mediator; 2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and 3) the between-trial level variance-covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings. PMID:28239330

Statistical analysis of secondary particle distributions in relativistic nucleus-nucleus collisions

NASA Technical Reports Server (NTRS)

Mcguire, Stephen C.

1987-01-01

The use is described of several statistical techniques to characterize structure in the angular distributions of secondary particles from nucleus-nucleus collisions in the energy range 24 to 61 GeV/nucleon. The objective of this work was to determine whether there are correlations between emitted particle intensity and angle that may be used to support the existence of the quark gluon plasma. The techniques include chi-square null hypothesis tests, the method of discrete Fourier transform analysis, and fluctuation analysis. We have also used the method of composite unit vectors to test for azimuthal asymmetry in a data set of 63 JACEE-3 events. Each method is presented in a manner that provides the reader with some practical detail regarding its application. Of those events with relatively high statistics, Fe approaches 0 at 55 GeV/nucleon was found to possess an azimuthal distribution with a highly non-random structure. No evidence of non-statistical fluctuations was found in the pseudo-rapidity distributions of the events studied. It is seen that the most effective application of these methods relies upon the availability of many events or single events that possess very high multiplicities.

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

NASA Astrophysics Data System (ADS)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

Descriptive data analysis.

PubMed

Thompson, Cheryl Bagley

2009-01-01

This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.

Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

PubMed

Westfall, Jacob; Kenny, David A; Judd, Charles M

2014-10-01

Researchers designing experiments in which a sample of participants responds to a sample of stimuli are faced with difficult questions about optimal study design. The conventional procedures of statistical power analysis fail to provide appropriate answers to these questions because they are based on statistical models in which stimuli are not assumed to be a source of random variation in the data, models that are inappropriate for experiments involving crossed random factors of participants and stimuli. In this article, we present new methods of power analysis for designs with crossed random factors, and we give detailed, practical guidance to psychology researchers planning experiments in which a sample of participants responds to a sample of stimuli. We extensively examine 5 commonly used experimental designs, describe how to estimate statistical power in each, and provide power analysis results based on a reasonable set of default parameter values. We then develop general conclusions and formulate rules of thumb concerning the optimal design of experiments in which a sample of participants responds to a sample of stimuli. We show that in crossed designs, statistical power typically does not approach unity as the number of participants goes to infinity but instead approaches a maximum attainable power value that is possibly small, depending on the stimulus sample. We also consider the statistical merits of designs involving multiple stimulus blocks. Finally, we provide a simple and flexible Web-based power application to aid researchers in planning studies with samples of stimuli.

Identification of the isomers using principal component analysis (PCA) method

NASA Astrophysics Data System (ADS)

Kepceoǧlu, Abdullah; Gündoǧdu, Yasemin; Ledingham, Kenneth William David; Kilic, Hamdi Sukur

2016-03-01

In this work, we have carried out a detailed statistical analysis for experimental data of mass spectra from xylene isomers. Principle Component Analysis (PCA) was used to identify the isomers which cannot be distinguished using conventional statistical methods for interpretation of their mass spectra. Experiments have been carried out using a linear TOF-MS coupled to a femtosecond laser system as an energy source for the ionisation processes. We have performed experiments and collected data which has been analysed and interpreted using PCA as a multivariate analysis of these spectra. This demonstrates the strength of the method to get an insight for distinguishing the isomers which cannot be identified using conventional mass analysis obtained through dissociative ionisation processes on these molecules. The PCA results dependending on the laser pulse energy and the background pressure in the spectrometers have been presented in this work.

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

Experimental design, power and sample size for animal reproduction experiments.

PubMed

Chapman, Phillip L; Seidel, George E

2008-01-01

The present paper concerns statistical issues in the design of animal reproduction experiments, with emphasis on the problems of sample size determination and power calculations. We include examples and non-technical discussions aimed at helping researchers avoid serious errors that may invalidate or seriously impair the validity of conclusions from experiments. Screen shots from interactive power calculation programs and basic SAS power calculation programs are presented to aid in understanding statistical power and computing power in some common experimental situations. Practical issues that are common to most statistical design problems are briefly discussed. These include one-sided hypothesis tests, power level criteria, equality of within-group variances, transformations of response variables to achieve variance equality, optimal specification of treatment group sizes, 'post hoc' power analysis and arguments for the increased use of confidence intervals in place of hypothesis tests.

Revised Perturbation Statistics for the Global Scale Atmospheric Model

NASA Technical Reports Server (NTRS)

Justus, C. G.; Woodrum, A.

1975-01-01

Magnitudes and scales of atmospheric perturbations about the monthly mean for the thermodynamic variables and wind components are presented by month at various latitudes. These perturbation statistics are a revision of the random perturbation data required for the global scale atmospheric model program and are from meteorological rocket network statistical summaries in the 22 to 65 km height range and NASA grenade and pitot tube data summaries in the region up to 90 km. The observed perturbations in the thermodynamic variables were adjusted to make them consistent with constraints required by the perfect gas law and the hydrostatic equation. Vertical scales were evaluated by Buell's depth of pressure system equation and from vertical structure function analysis. Tables of magnitudes and vertical scales are presented for each month at latitude 10, 30, 50, 70, and 90 degrees.

Method for data analysis in different institutions: example of image guidance of prostate cancer patients.

PubMed

Piotrowski, T; Rodrigues, G; Bajon, T; Yartsev, S

2014-03-01

Multi-institutional collaborations allow for more information to be analyzed but the data from different sources may vary in the subgroup sizes and/or conditions of measuring. Rigorous statistical analysis is required for pooling the data in a larger set. Careful comparison of all the components of the data acquisition is indispensable: identical conditions allow for enlargement of the database with improved statistical analysis, clearly defined differences provide opportunity for establishing a better practice. The optimal sequence of required normality, asymptotic normality, and independence tests is proposed. An example of analysis of six subgroups of position corrections in three directions obtained during image guidance procedures for 216 prostate cancer patients from two institutions is presented. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Integrating statistical and clinical research elements in intervention-related grant applications: summary from an NIMH workshop.

PubMed

Sherrill, Joel T; Sommers, David I; Nierenberg, Andrew A; Leon, Andrew C; Arndt, Stephan; Bandeen-Roche, Karen; Greenhouse, Joel; Guthrie, Donald; Normand, Sharon-Lise; Phillips, Katharine A; Shear, M Katherine; Woolson, Robert

2009-01-01

The authors summarize points for consideration generated in a National Institute of Mental Health (NIMH) workshop convened to provide an opportunity for reviewers from different disciplines-specifically clinical researchers and statisticians-to discuss how their differing and complementary expertise can be well integrated in the review of intervention-related grant applications. A 1-day workshop was convened in October, 2004. The workshop featured panel presentations on key topics followed by interactive discussion. This article summarizes the workshop and subsequent discussions, which centered on topics including weighting the statistics/data analysis elements of an application in the assessment of the application's overall merit; the level of statistical sophistication appropriate to different stages of research and for different funding mechanisms; some key considerations in the design and analysis portions of applications; appropriate statistical methods for addressing essential questions posed by an application; and the role of the statistician in the application's development, study conduct, and interpretation and dissemination of results. A number of key elements crucial to the construction and review of grant applications were identified. It was acknowledged that intervention-related studies unavoidably involve trade-offs. Reviewers are helped when applications acknowledge such trade-offs and provide good rationale for their choices. Clear linkage among the design, aims, hypotheses, and data analysis plan and avoidance of disconnections among these elements also strengthens applications. The authors identify multiple points to consider when constructing intervention-related grant applications. The points are presented here as questions and do not reflect institute policy or comprise a list of best practices, but rather represent points for consideration.

MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing.

PubMed

Zackay, Arie; Steinhoff, Christine

2010-12-15

Exploration of DNA methylation and its impact on various regulatory mechanisms has become a very active field of research. Simultaneously there is an arising need for tools to process and analyse the data together with statistical investigation and visualisation. MethVisual is a new application that enables exploratory analysis and intuitive visualization of DNA methylation data as is typically generated by bisulfite sequencing. The package allows the import of DNA methylation sequences, aligns them and performs quality control comparison. It comprises basic analysis steps as lollipop visualization, co-occurrence display of methylation of neighbouring and distant CpG sites, summary statistics on methylation status, clustering and correspondence analysis. The package has been developed for methylation data but can be also used for other data types for which binary coding can be inferred. The application of the package, as well as a comparison to existing DNA methylation analysis tools and its workflow based on two datasets is presented in this paper. The R package MethVisual offers various analysis procedures for data that can be binarized, in particular for bisulfite sequenced methylation data. R/Bioconductor has become one of the most important environments for statistical analysis of various types of biological and medical data. Therefore, any data analysis within R that allows the integration of various data types as provided from different technological platforms is convenient. It is the first and so far the only specific package for DNA methylation analysis, in particular for bisulfite sequenced data available in R/Bioconductor enviroment. The package is available for free at http://methvisual.molgen.mpg.de/ and from the Bioconductor Consortium http://www.bioconductor.org.

MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing

PubMed Central

2010-01-01

Background Exploration of DNA methylation and its impact on various regulatory mechanisms has become a very active field of research. Simultaneously there is an arising need for tools to process and analyse the data together with statistical investigation and visualisation. Findings MethVisual is a new application that enables exploratory analysis and intuitive visualization of DNA methylation data as is typically generated by bisulfite sequencing. The package allows the import of DNA methylation sequences, aligns them and performs quality control comparison. It comprises basic analysis steps as lollipop visualization, co-occurrence display of methylation of neighbouring and distant CpG sites, summary statistics on methylation status, clustering and correspondence analysis. The package has been developed for methylation data but can be also used for other data types for which binary coding can be inferred. The application of the package, as well as a comparison to existing DNA methylation analysis tools and its workflow based on two datasets is presented in this paper. Conclusions The R package MethVisual offers various analysis procedures for data that can be binarized, in particular for bisulfite sequenced methylation data. R/Bioconductor has become one of the most important environments for statistical analysis of various types of biological and medical data. Therefore, any data analysis within R that allows the integration of various data types as provided from different technological platforms is convenient. It is the first and so far the only specific package for DNA methylation analysis, in particular for bisulfite sequenced data available in R/Bioconductor enviroment. The package is available for free at http://methvisual.molgen.mpg.de/ and from the Bioconductor Consortium http://www.bioconductor.org. PMID:21159174

Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data.

PubMed

Excoffier, L; Smouse, P E; Quattro, J M

1992-06-01

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.

Full-text publication of abstracts presented at European Orthodontic Society congresses.

PubMed

Livas, Christos; Pandis, Nikolaos; Ren, Yijin

2014-10-01

Empirical evidence has indicated that only a subsample of studies conducted reach full-text publication and this phenomenon has become known as publication bias. A form of publication bias is the selectively delayed full publication of conference abstracts. The objective of this article was to examine the publication status of oral abstracts and poster-presentation abstracts, included in the scientific program of the 82nd and 83rd European Orthodontic Society (EOS) congresses, held in 2006 and 2007, and to identify factors associated with full-length publication. A systematic search of PubMed and Google Scholar databases was performed in April 2013 using author names and keywords from the abstract title to locate abstract and full-article publications. Information regarding mode of presentation, type of affiliation, geographical origin, statistical results, and publication details were collected and analyzed using univariable and multivariable logistic regression. Approximately 51 per cent of the EOS 2006 and 55 per cent of the EOS 2007 abstracts appeared in print more than 5 years post congress. A mean period of 1.32 years elapsed between conference and publication date. Mode of presentation (oral or poster), use of statistical analysis, and research subject area were significant predictors for publication success. Inherent discrepancies of abstract reporting, mainly related to presentation of preliminary results and incomplete description of methods, may be considered in analogous studies. On average 52.2 per cent of the abstracts presented at the two EOS conferences reached full publication. Abstracts presented orally, including statistical analysis, were more likely to get published. © The Author 2013. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida

NASA Astrophysics Data System (ADS)

Sayemuzzaman, M.; Ye, M.

2015-12-01

The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface waters can be undertaken.

ASCS online fault detection and isolation based on an improved MPCA

NASA Astrophysics Data System (ADS)

Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

2014-09-01

Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

Climate Change Education in Earth System Science

NASA Astrophysics Data System (ADS)

Hänsel, Stephanie; Matschullat, Jörg

2013-04-01

The course "Atmospheric Research - Climate Change" is offered to master Earth System Science students within the specialisation "Climate and Environment" at the Technical University Bergakademie Freiberg. This module takes a comprehensive approach to climate sciences, reaching from the natural sciences background of climate change via the social components of the issue to the statistical analysis of changes in climate parameters. The course aims at qualifying the students to structure the physical and chemical basics of the climate system including relevant feedbacks. The students can evaluate relevant drivers of climate variability and change on various temporal and spatial scales and can transform knowledge from climate history to the present and the future. Special focus is given to the assessment of uncertainties related to climate observations and projections as well as the specific challenges of extreme weather and climate events. At the end of the course the students are able to critically reflect and evaluate climate change related results of scientific studies and related issues in media. The course is divided into two parts - "Climate Change" and "Climate Data Analysis" and encompasses two lectures, one seminar and one exercise. The weekly "Climate change" lecture transmits the physical and chemical background for climate variation and change. (Pre)historical, observed and projected climate changes and their effects on various sectors are being introduced and discussed regarding their implications for society, economics, ecology and politics. The related seminar presents and discusses the multiple reasons for controversy in climate change issues, based on various texts. Students train the presentation of scientific content and the discussion of climate change aspects. The biweekly lecture on "Climate data analysis" introduces the most relevant statistical tools and methods in climate science. Starting with checking data quality via tools of exploratory data analysis the approaches on climate time series, trend analysis and extreme events analysis are explained. Tools to describe relations within the data sets and significance tests further corroborate this. Within the weekly exercises that have to be prepared at home, the students work with self-selected climate data sets and apply the learned methods. The presentation and discussion of intermediate results by the students is as much part of the exercises as the illustration of possible methodological procedures by the teacher using exemplary data sets. The total time expenditure of the course is 270 hours with 90 attendance hours. The remainder consists of individual studies, e.g., preparation of discussions and presentations, statistical data analysis, and scientific writing. Different forms of examination are applied including written or oral examination, scientific report, presentation and portfolio work.

Accuracy of trace element determinations in alternate fuels

NASA Technical Reports Server (NTRS)

Greenbauer-Seng, L. A.

1980-01-01

A review of the techniques used at Lewis Research Center (LeRC) in trace metals analysis is presented, including the results of Atomic Absorption Spectrometry and DC Arc Emission Spectrometry of blank levels and recovery experiments for several metals. The design of an Interlaboratory Study conducted by LeRC is presented. Several factors were investigated, including: laboratory, analytical technique, fuel type, concentration, and ashing additive. Conclusions drawn from the statistical analysis will help direct research efforts toward those areas most responsible for the poor interlaboratory analytical results.

Distributed video data fusion and mining

NASA Astrophysics Data System (ADS)

Chang, Edward Y.; Wang, Yuan-Fang; Rodoplu, Volkan

2004-09-01

This paper presents an event sensing paradigm for intelligent event-analysis in a wireless, ad hoc, multi-camera, video surveillance system. In particilar, we present statistical methods that we have developed to support three aspects of event sensing: 1) energy-efficient, resource-conserving, and robust sensor data fusion and analysis, 2) intelligent event modeling and recognition, and 3) rapid deployment, dynamic configuration, and continuous operation of the camera networks. We outline our preliminary results, and discuss future directions that research might take.

Stokes-correlometry of polarization-inhomogeneous objects

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Dubolazov, A.; Bodnar, G. B.; Bachynskiy, V. T.; Vanchulyak, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of Stokes-correlometry description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of modulus (MSV) and phase (PhSV) of complex Stokes vector of skeletal muscle tissue. It was defined the values and ranges of changes of statistic moments of the 1st-4th orders, which characterize the distributions of values of MSV and PhSV. The second part presents the data of statistic analysis of the distributions of modulus MSV and PhSV. It was defined the objective criteria of differentiation of samples with urinary incontinence.

Statistical evaluation of GLONASS amplitude scintillation over low latitudes in the Brazilian territory

NASA Astrophysics Data System (ADS)

de Oliveira Moraes, Alison; Muella, Marcio T. A. H.; de Paula, Eurico R.; de Oliveira, César B. A.; Terra, William P.; Perrella, Waldecir J.; Meibach-Rosa, Pâmela R. P.

2018-04-01

The ionospheric scintillation, generated by the ionospheric plasma irregularities, affects the radio signals that pass through it. Their effects are widely studied in the literature with two different approaches. The first one deals with the use of radio signals to study and understand the morphology of this phenomenon, while the second one seeks to understand and model how much this phenomenon interferes in the radio signals and consequently in the services to which these systems work. The interest of several areas, particularly to those that are life critical, has increased using the concept of satellite multi-constellation, which consists of receiving, processing and using data from different navigation and positioning systems. Although there is a vast literature analyzing the effects of ionospheric scintillation on satellite navigation systems, the number of studies using signals received from the Russian satellite positioning system (named GLONASS) is still very rare. This work presents for the first time in the Brazilian low-latitude sector a statistical analysis of ionospheric scintillation data for all levels of magnetic activities obtained by a set of scintillation monitors that receive signals from the GLONASS system. In this study, data collected from four stations were used in the analysis; Fortaleza, Presidente Prudente, São José dos Campos and Porto Alegre. The GLONASS L-band signals were analyzed for the period from December 21, 2012 to June 20, 2016, which includes the peak of the solar cycle 24 that occurred in 2014. The main characteristics of scintillation presented in this study include: (1) the statistical evaluation of seasonal and solar activity, showing the chances that an user on similar geophysical conditions may be susceptible to the effects of ionospheric scintillation; (2) a temporal analysis based on the local time distribution of scintillation at different seasons and intensity levels; and (3) the evaluation of number of simultaneously affected channels and its effects on the dilution of precision (DOP) for GNSS users are also presented in order to alert the timetables in which navigation will be most susceptible to such effects, as well as statistics on simultaneously affected channels. Relevant results about these statistical characteristics of scintillation are presented and analyzed providing relevant information about availability of a navigation system.

Global map of lithosphere thermal thickness on a 1 deg x 1 deg grid - digitally available

NASA Astrophysics Data System (ADS)

Artemieva, Irina

2014-05-01

This presentation reports a 1 deg ×1 deg global thermal model for the continental lithosphere (TC1). The model is digitally available from the author's web-site: www.lithosphere.info. Geotherms for continental terranes of different ages (early Archean to present) are constrained by reliable data on borehole heat flow measurements (Artemieva and Mooney, 2001), checked with the original publications for data quality, and corrected for paleo-temperature effects where needed. These data are supplemented by cratonic geotherms based on xenolith data. Since heat flow measurements cover not more than half of the continents, the remaining areas (ca. 60% of the continents) are filled by the statistical numbers derived from the thermal model constrained by borehole data. Continental geotherms are statistically analyzed as a function of age and are used to estimate lithospheric temperatures in continental regions with no or low quality heat flow data. This analysis requires knowledge of lithosphere age globally. A compilation of tectono-thermal ages of lithospheric terranes on a 1 deg × 1 deg grid forms the basis for the statistical analysis. It shows that, statistically, lithospheric thermal thickness z (in km) depends on tectono-thermal age t (in Ma) as: z=0.04t+93.6. This relationship formed the basis for a global thermal model of the continental lithosphere (TC1). Statistical analysis of continental geotherms also reveals that this relationship holds for the Archean cratons in general, but not in detail. Particularly, thick (more than 250 km) lithosphere is restricted solely to young Archean terranes (3.0-2.6 Ga), while in old Archean cratons (3.6-3.0 Ga) lithospheric roots do not extend deeper than 200-220 km. The TC1 model is presented by a set of maps, which show significant thermal heterogeneity within continental upper mantle. The strongest lateral temperature variations (as large as 800 deg C) are typical of the shallow mantle (depth less than 100 km). A map of the depth to a 600 deg C isotherm in continental upper mantle is presented as a proxy to the elastic thickness of the cratonic lithosphere, in which flexural rigidity is dominated by olivine rheology of the mantle. The TC1 model of the lithosphere thickness is used to calculate the growth and preservation rates of the lithosphere since the Archean.

An analysis of Iowa's forest resources, 1990.

Treesearch

Earl C. Leatherberry; Sue M. Roussopoulos; John S. Jr. Spencer

1992-01-01

The third Iowa forest inventory found 2.1 million acres of forest land in 1990, of which 1.9 million acres is timberland. Growing-stock volume on timberland increased from 1.1 to 1.7 billion cubic feet between 1974 and 1990, a gain of 46%. Presents analysis and statistics on forest area, timber volume, growth, removals, mortality, and projections.

Sample Size Calculations for Precise Interval Estimation of the Eta-Squared Effect Size

ERIC Educational Resources Information Center

Shieh, Gwowen

2015-01-01

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Implementation of Head Start Planned Variation: 1970-1971. Part II.

ERIC Educational Resources Information Center

Lukas, Carol Van Deusen; Wohlleb, Cynthia

This volume of appendices is Part II of a study of program implementation in 12 models of Head Start Planned Variation. It presents details of the data analysis, copies of data collection instruments, and additional analyses and statistics. The appendices are: (A) Analysis of Variance Designs, (B) Copies of Instruments, (C) Additional Analyses,…

An exploratory investigation of weight estimation techniques for hypersonic flight vehicles

NASA Technical Reports Server (NTRS)

Cook, E. L.

1981-01-01

The three basic methods of weight prediction (fixed-fraction, statistical correlation, and point stress analysis) and some of the computer programs that have been developed to implement them are discussed. A modified version of the WAATS (Weights Analysis of Advanced Transportation Systems) program is presented, along with input data forms and an example problem.

Prerequisites for Systems Analysts: Analytic and Management Demands of a New Approach to Educational Administration.

ERIC Educational Resources Information Center

Ammentorp, William

There is much to be gained by using systems analysis in educational administration. Most administrators, presently relying on classical statistical techniques restricted to problems having few variables, should be trained to use more sophisticated tools such as systems analysis. The systems analyst, interested in the basic processes of a group or…

A Content Analysis of Dissertations in the Field of Educational Technology: The Case of Turkey

ERIC Educational Resources Information Center

Durak, Gurhan; Cankaya, Serkan; Yunkul, Eyup; Misirli, Zeynel Abidin

2018-01-01

The present study aimed at conducting content analysis on dissertations carried out so far in the field of Educational Technology in Turkey. A total of 137 dissertations were examined to determine the key words, academic discipline, research areas, theoretical frameworks, research designs and models, statistical analyses, data collection tools,…

Crash analysis, statistics & information notebook 2008

DOT National Transportation Integrated Search

2008-01-01

Traditionally crash data is often presented as single fact sheets highlighting a single factor such as Vehicle Type or Road Type. This document will try to show how the risk factors interrelate to produce a crash. Complete detailed analys...

Ohio traffic crash facts, 2007

DOT National Transportation Integrated Search

2008-05-07

The Ohio Department of Public Safety is pleased to present the 2007 Ohio Traffic Crash : Facts Book, an in-depth highway safety statistical profile and analysis compiled from : data supplied by law enforcement agencies from across the state. : This a...

Ohio traffic crash facts, 2008

DOT National Transportation Integrated Search

2009-07-01

The Ohio Department of Public Safety is pleased to present the 2008 Ohio Traffic Crash : Facts Book, an in-depth highway safety statistical profile and analysis compiled from : data supplied by law enforcement agencies from across the state. This ann...

Ohio traffic crash facts, 2009

DOT National Transportation Integrated Search

2010-11-01

The Ohio Department of Public Safety is pleased to present the 2009 Ohio Traffic Crash Facts Book, an in-depth highway safety statistical profile and analysis compiled from data supplied by law enforcement agencies from across the state. This annual ...

Spectral analysis of groove spacing on Ganymede

NASA Technical Reports Server (NTRS)

Grimm, R. E.

1984-01-01

The technique used to analyze groove spacing on Ganymede is presented. Data from Voyager images are used determine the surface topography and position of the grooves. Power spectal estimates are statistically analyzed and sample data is included.

Reproducible research in vadose zone sciences

USDA-ARS?s Scientific Manuscript database

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building o...

Optimizing construction quality management of pavements using mechanistic performance analysis.

DOT National Transportation Integrated Search

2004-08-01

This report presents a statistical-based algorithm that was developed to reconcile the results from several pavement performance models used in the state of practice with systematic process control techniques. These algorithms identify project-specif...

Statistical properties of the radiation belt seed population

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, A. J.; Spence, H. E.; Huang, C. -L.

Here, we present a statistical analysis of phase space density data from the first 26 months of the Van Allen Probes mission. In particular, we investigate the relationship between the tens and hundreds of keV seed electrons and >1 MeV core radiation belt electron population. Using a cross-correlation analysis, we find that the seed and core populations are well correlated with a coefficient of ≈0.73 with a time lag of 10–15 h. We present evidence of a seed population threshold that is necessary for subsequent acceleration. The depth of penetration of the seed population determines the inner boundary of themore » acceleration process. However, we show that an enhanced seed population alone is not enough to produce acceleration in the higher energies, implying that the seed population of hundreds of keV electrons is only one of several conditions required for MeV electron radiation belt acceleration.« less

Statistical properties of the radiation belt seed population

DOE PAGES

Boyd, A. J.; Spence, H. E.; Huang, C. -L.; ...

2016-07-25

Here, we present a statistical analysis of phase space density data from the first 26 months of the Van Allen Probes mission. In particular, we investigate the relationship between the tens and hundreds of keV seed electrons and >1 MeV core radiation belt electron population. Using a cross-correlation analysis, we find that the seed and core populations are well correlated with a coefficient of ≈0.73 with a time lag of 10–15 h. We present evidence of a seed population threshold that is necessary for subsequent acceleration. The depth of penetration of the seed population determines the inner boundary of themore » acceleration process. However, we show that an enhanced seed population alone is not enough to produce acceleration in the higher energies, implying that the seed population of hundreds of keV electrons is only one of several conditions required for MeV electron radiation belt acceleration.« less

Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux

PubMed Central

Lee, Jonghwan; Jiang, James Y.; Wu, Weicheng; Lesage, Frederic; Boas, David A.

2014-01-01

We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation. PMID:24761298

Singular Spectrum Analysis for Astronomical Time Series: Constructing a Parsimonious Hypothesis Test

NASA Astrophysics Data System (ADS)

Greco, G.; Kondrashov, D.; Kobayashi, S.; Ghil, M.; Branchesi, M.; Guidorzi, C.; Stratta, G.; Ciszak, M.; Marino, F.; Ortolan, A.

We present a data-adaptive spectral method - Monte Carlo Singular Spectrum Analysis (MC-SSA) - and its modification to tackle astrophysical problems. Through numerical simulations we show the ability of the MC-SSA in dealing with 1/f β power-law noise affected by photon counting statistics. Such noise process is simulated by a first-order autoregressive, AR(1) process corrupted by intrinsic Poisson noise. In doing so, we statistically estimate a basic stochastic variation of the source and the corresponding fluctuations due to the quantum nature of light. In addition, MC-SSA test retains its effectiveness even when a significant percentage of the signal falls below a certain level of detection, e.g., caused by the instrument sensitivity. The parsimonious approach presented here may be broadly applied, from the search for extrasolar planets to the extraction of low-intensity coherent phenomena probably hidden in high energy transients.

GASP cloud- and particle-encounter statistics and their application to LFC aircraft studies. Volume 2: Appendixes

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastron, G. D.; Davis, R. E.; Holdeman, J. D.

1984-01-01

Summary studies are presented for the entire cloud observation archive from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle-concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud-encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long-range airline routes, and to assess the probability and extent of laminaar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical. This report is presented in two volumes. Volume I contains the narrative, analysis, and conclusions. Volume II contains five supporting appendixes.

Effect and safety of early weight-bearing on the outcome after open-wedge high tibial osteotomy: a systematic review and meta-analysis.

PubMed

Lee, O-Sung; Ahn, Soyeon; Lee, Yong Seuk

2017-07-01

The purpose of this systematic review and meta-analysis was to evaluate the effectiveness and safety of early weight-bearing by comparing clinical and radiological outcomes between early and traditional delayed weight-bearing after OWHTO. A rigorous and systematic approach was used. The methodological quality was also assessed. Results that are possible to be compared in two or more than two articles were presented as forest plots. A 95% confidence interval was calculated for each effect size, and we calculated the I 2 statistic, which presents the percentage of total variation attributable to the heterogeneity among studies. The random-effects model was used to calculate the effect size. Six articles were included in the final analysis. All case groups were composed of early full weight-bearing within 2 weeks. All control groups were composed of late full weight-bearing between 6 weeks and 2 months. Pooled analysis was possible for the improvement in Lysholm score, but there was no statistically significant difference shown between groups. Other clinical results were also similar between groups. Four studies reported mechanical femorotibial angle (mFTA) and this result showed no statistically significant difference between groups in the pooled analysis. Furthermore, early weight-bearing showed more favorable results in some radiologic results (osseointegration and patellar height) and complications (thrombophlebitis and recurrence). Our analysis supports that early full weight-bearing after OWHTO using a locking plate leads to improvement in outcomes and was comparable to the delayed weight-bearing in terms of clinical and radiological outcomes. On the contrary, early weight-bearing was more favorable with respect to some radiologic parameters and complications compared with delayed weight-bearing.

Rescaled earthquake recurrence time statistics: application to microrepeaters

NASA Astrophysics Data System (ADS)

Goltz, Christian; Turcotte, Donald L.; Abaimov, Sergey G.; Nadeau, Robert M.; Uchida, Naoki; Matsuzawa, Toru

2009-01-01

Slip on major faults primarily occurs during `characteristic' earthquakes. The recurrence statistics of characteristic earthquakes play an important role in seismic hazard assessment. A major problem in determining applicable statistics is the short sequences of characteristic earthquakes that are available worldwide. In this paper, we introduce a rescaling technique in which sequences can be superimposed to establish larger numbers of data points. We consider the Weibull and log-normal distributions, in both cases we rescale the data using means and standard deviations. We test our approach utilizing sequences of microrepeaters, micro-earthquakes which recur in the same location on a fault. It seems plausible to regard these earthquakes as a miniature version of the classic characteristic earthquakes. Microrepeaters are much more frequent than major earthquakes, leading to longer sequences for analysis. In this paper, we present results for the analysis of recurrence times for several microrepeater sequences from Parkfield, CA as well as NE Japan. We find that, once the respective sequence can be considered to be of sufficient stationarity, the statistics can be well fitted by either a Weibull or a log-normal distribution. We clearly demonstrate this fact by our technique of rescaled combination. We conclude that the recurrence statistics of the microrepeater sequences we consider are similar to the recurrence statistics of characteristic earthquakes on major faults.

The analysis of professional competencies of a lecturer in adult education.

PubMed

Žeravíková, Iveta; Tirpáková, Anna; Markechová, Dagmar

2015-01-01

In this article, we present the andragogical research project and evaluation of its results using nonparametric statistical methods and the semantic differential method. The presented research was realized in the years 2012-2013 in the dissertation of I. Žeravíková: Analysis of professional competencies of lecturer and creating his competence profile (Žeravíková 2013), and its purpose was based on the analysis of work activities of a lecturer to identify his most important professional competencies and to create a suggestion of competence profile of a lecturer in adult education.

Stationary statistical theory of two-surface multipactor regarding all impacts for efficient threshold analysis

NASA Astrophysics Data System (ADS)

Lin, Shu; Wang, Rui; Xia, Ning; Li, Yongdong; Liu, Chunliang

2018-01-01

Statistical multipactor theories are critical prediction approaches for multipactor breakdown determination. However, these approaches still require a negotiation between the calculation efficiency and accuracy. This paper presents an improved stationary statistical theory for efficient threshold analysis of two-surface multipactor. A general integral equation over the distribution function of the electron emission phase with both the single-sided and double-sided impacts considered is formulated. The modeling results indicate that the improved stationary statistical theory can not only obtain equally good accuracy of multipactor threshold calculation as the nonstationary statistical theory, but also achieve high calculation efficiency concurrently. By using this improved stationary statistical theory, the total time consumption in calculating full multipactor susceptibility zones of parallel plates can be decreased by as much as a factor of four relative to the nonstationary statistical theory. It also shows that the effect of single-sided impacts is indispensable for accurate multipactor prediction of coaxial lines and also more significant for the high order multipactor. Finally, the influence of secondary emission yield (SEY) properties on the multipactor threshold is further investigated. It is observed that the first cross energy and the energy range between the first cross and the SEY maximum both play a significant role in determining the multipactor threshold, which agrees with the numerical simulation results in the literature.

Analysis of the Database of Theses and Dissertations from DME/UFSCAR about Astronomy Education

NASA Astrophysics Data System (ADS)

Rodrigues Ferreira, Orlando; Voelzke, Marcos Rincon

2013-11-01

The paper presents a brief analysis of the "Database of Theses and Dissertations about Astronomy Education" from the Department of Teaching Methodology (DME) of the Federal University of São Carlos(UFSCar). This kind of study made it possible to develop new analysis and statistical data, as well as to conduct a rating of Brazilian institutions that produce academic work in the area.

The CTS 11.7 GHz angle of arrival experiment

NASA Technical Reports Server (NTRS)

Kwan, B. W.; Hodge, D. B.

1981-01-01

The objective of the experiment was to determine the statistical behavior of attenuation and angle of arrival on an Earth-space propagation path using the CTS 11.7 GHz beacon. Measurements performed from 1976 to 1978 form the data base for analysis. The statistics of the signal attenuation and phase variations due to atmospheric disturbances are presented. Rainfall rate distributions are also included to provide a link between the above effects on wave propagation and meteorological conditions.

Radiation from quantum weakly dynamical horizons in loop quantum gravity.

PubMed

Pranzetti, Daniele

2012-07-06

We provide a statistical mechanical analysis of quantum horizons near equilibrium in the grand canonical ensemble. By matching the description of the nonequilibrium phase in terms of weakly dynamical horizons with a local statistical framework, we implement loop quantum gravity dynamics near the boundary. The resulting radiation process provides a quantum gravity description of the horizon evaporation. For large black holes, the spectrum we derive presents a discrete structure which could be potentially observable.

A statistical-based scheduling algorithm in automated data path synthesis

NASA Technical Reports Server (NTRS)

Jeon, Byung Wook; Lursinsap, Chidchanok

1992-01-01

In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.

ACCOUNTING FOR CALIBRATION UNCERTAINTIES IN X-RAY ANALYSIS: EFFECTIVE AREAS IN SPECTRAL FITTING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Hyunsook; Kashyap, Vinay L.; Drake, Jeremy J.

2011-04-20

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here, we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can bemore » applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.« less

Analyzing Dyadic Sequence Data—Research Questions and Implied Statistical Models

PubMed Central

Fuchs, Peter; Nussbeck, Fridtjof W.; Meuwly, Nathalie; Bodenmann, Guy

2017-01-01

The analysis of observational data is often seen as a key approach to understanding dynamics in romantic relationships but also in dyadic systems in general. Statistical models for the analysis of dyadic observational data are not commonly known or applied. In this contribution, selected approaches to dyadic sequence data will be presented with a focus on models that can be applied when sample sizes are of medium size (N = 100 couples or less). Each of the statistical models is motivated by an underlying potential research question, the most important model results are presented and linked to the research question. The following research questions and models are compared with respect to their applicability using a hands on approach: (I) Is there an association between a particular behavior by one and the reaction by the other partner? (Pearson Correlation); (II) Does the behavior of one member trigger an immediate reaction by the other? (aggregated logit models; multi-level approach; basic Markov model); (III) Is there an underlying dyadic process, which might account for the observed behavior? (hidden Markov model); and (IV) Are there latent groups of dyads, which might account for observing different reaction patterns? (mixture Markov; optimal matching). Finally, recommendations for researchers to choose among the different models, issues of data handling, and advises to apply the statistical models in empirical research properly are given (e.g., in a new r-package “DySeq”). PMID:28443037

Trial Sequential Analysis in systematic reviews with meta-analysis.

PubMed

Wetterslev, Jørn; Jakobsen, Janus Christian; Gluud, Christian

2017-03-06

Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors) and too many false negative conclusions (type II errors). We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D 2 ) measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in systematic reviews with traditional meta-analyses can be reduced using Trial Sequential Analysis. Several empirical studies have demonstrated that the Trial Sequential Analysis provides better control of type I errors and of type II errors than the traditional naïve meta-analysis. Trial Sequential Analysis represents analysis of meta-analytic data, with transparent assumptions, and better control of type I and type II errors than the traditional meta-analysis using naïve unadjusted confidence intervals.

Statistical principle and methodology in the NISAN system.

PubMed Central

Asano, C

1979-01-01

The NISAN system is a new interactive statistical analysis program package constructed by an organization of Japanese statisticans. The package is widely available for both statistical situations, confirmatory analysis and exploratory analysis, and is planned to obtain statistical wisdom and to choose optimal process of statistical analysis for senior statisticians. PMID:540594

Statistical tools for transgene copy number estimation based on real-time PCR.

PubMed

Yuan, Joshua S; Burris, Jason; Stewart, Nathan R; Mentewab, Ayalew; Stewart, C Neal

2007-11-01

As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. Three experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination. These statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Public Concepts of the Values and Costs of Higher Education, 1963-1974. A Preliminary Analysis.

ERIC Educational Resources Information Center

Minor, Michael J.; Murray, James R.

Statistical data are presented on interviews conducted through the Continuous National Survey (CNS) at the National Opinion Research Center in Chicago and based on results reprinted from "Public Concepts of the Values and Costs of Higher Education," by Angus Campbell and William C. Eckerman. The CNS results presented in this report are…

Recovering incomplete data using Statistical Multiple Imputations (SMI): a case study in environmental chemistry.

PubMed

Mercer, Theresa G; Frostick, Lynne E; Walmsley, Anthony D

2011-10-15

This paper presents a statistical technique that can be applied to environmental chemistry data where missing values and limit of detection levels prevent the application of statistics. A working example is taken from an environmental leaching study that was set up to determine if there were significant differences in levels of leached arsenic (As), chromium (Cr) and copper (Cu) between lysimeters containing preservative treated wood waste and those containing untreated wood. Fourteen lysimeters were setup and left in natural conditions for 21 weeks. The resultant leachate was analysed by ICP-OES to determine the As, Cr and Cu concentrations. However, due to the variation inherent in each lysimeter combined with the limits of detection offered by ICP-OES, the collected quantitative data was somewhat incomplete. Initial data analysis was hampered by the number of 'missing values' in the data. To recover the dataset, the statistical tool of Statistical Multiple Imputation (SMI) was applied, and the data was re-analysed successfully. It was demonstrated that using SMI did not affect the variance in the data, but facilitated analysis of the complete dataset. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluating the statistical methodology of randomized trials on dentin hypersensitivity management.

PubMed

Matranga, Domenica; Matera, Federico; Pizzo, Giuseppe

2017-12-27

The present study aimed to evaluate the characteristics and quality of statistical methodology used in clinical studies on dentin hypersensitivity management. An electronic search was performed for data published from 2009 to 2014 by using PubMed, Ovid/MEDLINE, and Cochrane Library databases. The primary search terms were used in combination. Eligibility criteria included randomized clinical trials that evaluated the efficacy of desensitizing agents in terms of reducing dentin hypersensitivity. A total of 40 studies were considered eligible for assessment of quality statistical methodology. The four main concerns identified were i) use of nonparametric tests in the presence of large samples, coupled with lack of information about normality and equality of variances of the response; ii) lack of P-value adjustment for multiple comparisons; iii) failure to account for interactions between treatment and follow-up time; and iv) no information about the number of teeth examined per patient and the consequent lack of cluster-specific approach in data analysis. Owing to these concerns, statistical methodology was judged as inappropriate in 77.1% of the 35 studies that used parametric methods. Additional studies with appropriate statistical analysis are required to obtain appropriate assessment of the efficacy of desensitizing agents.

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

High-Density Signal Interface Electromagnetic Radiation Prediction for Electromagnetic Compatibility Evaluation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halligan, Matthew

Radiated power calculation approaches for practical scenarios of incomplete high- density interface characterization information and incomplete incident power information are presented. The suggested approaches build upon a method that characterizes power losses through the definition of power loss constant matrices. Potential radiated power estimates include using total power loss information, partial radiated power loss information, worst case analysis, and statistical bounding analysis. A method is also proposed to calculate radiated power when incident power information is not fully known for non-periodic signals at the interface. Incident data signals are modeled from a two-state Markov chain where bit state probabilities aremore » derived. The total spectrum for windowed signals is postulated as the superposition of spectra from individual pulses in a data sequence. Statistical bounding methods are proposed as a basis for the radiated power calculation due to the statistical calculation complexity to find a radiated power probability density function.« less

The statistical analysis of circadian phase and amplitude in constant-routine core-temperature data

NASA Technical Reports Server (NTRS)

Brown, E. N.; Czeisler, C. A.

1992-01-01

Accurate estimation of the phases and amplitude of the endogenous circadian pacemaker from constant-routine core-temperature series is crucial for making inferences about the properties of the human biological clock from data collected under this protocol. This paper presents a set of statistical methods based on a harmonic-regression-plus-correlated-noise model for estimating the phases and the amplitude of the endogenous circadian pacemaker from constant-routine core-temperature data. The methods include a Bayesian Monte Carlo procedure for computing the uncertainty in these circadian functions. We illustrate the techniques with a detailed study of a single subject's core-temperature series and describe their relationship to other statistical methods for circadian data analysis. In our laboratory, these methods have been successfully used to analyze more than 300 constant routines and provide a highly reliable means of extracting phase and amplitude information from core-temperature data.

Baseline estimation in flame's spectra by using neural networks and robust statistics

NASA Astrophysics Data System (ADS)

Garces, Hugo; Arias, Luis; Rojas, Alejandro

2014-09-01

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

Early-type galaxies in the Antlia cluster: catalogue and isophotal analysis

NASA Astrophysics Data System (ADS)

Calderón, Juan P.; Bassino, Lilia P.; Cellone, Sergio A.; Gómez, Matías

2018-06-01

We present a statistical isophotal analysis of 138 early-type galaxies in the Antlia cluster, located at a distance of ˜ 35 Mpc. The observational material consists of CCD images of four 36 × 36 arcmin2 fields obtained with the MOSAIC II camera at the Blanco 4-m telescope at Cerro Tololo Interamerican Observatory. Our present work supersedes previous Antlia studies in the sense that the covered area is four times larger, the limiting magnitude is MB ˜ -9.6 mag, and the surface photometry parameters of each galaxy are derived from Sérsic model fits extrapolated to infinity. In a companion previous study we focused on the scaling relations obtained by means of surface photometry, and now we present the data, on which the previous paper is based, the parameters of the isophotal fits as well as an isophotal analysis. For each galaxy, we derive isophotal shape parameters along the semimajor axis and search for correlations within different radial bins. Through extensive statistical tests, we also analyse the behaviour of these values against photometric and global parameters of the galaxies themselves. While some galaxies do display radial gradients in their ellipticity (ɛ) and/or their Fourier coefficients, differences in mean values between adjacent regions are not statistically significant. Regarding Fourier coefficients, dwarf galaxies usually display gradients between all adjacent regions, while non-dwarfs tend to show this behaviour just between the two outermost regions. Globally, there is no obvious correlation between Fourier coefficients and luminosity for the whole magnitude range (-12 ≳ MV ≳ -22); however, dwarfs display much higher dispersions at all radii.

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.

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.

Do climate extreme events foster violent civil conflicts? A coincidence analysis

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Donner, Reik V.

2014-05-01

Civil conflicts promoted by adverse environmental conditions represent one of the most important potential feedbacks in the global socio-environmental nexus. While the role of climate extremes as a triggering factor is often discussed, no consensus is yet reached about the cause-and-effect relation in the observed data record. Here we present results of a rigorous statistical coincidence analysis based on the Munich Re Inc. extreme events database and the Uppsala conflict data program. We report evidence for statistically significant synchronicity between climate extremes with high economic impact and violent conflicts for various regions, although no coherent global signal emerges from our analysis. Our results indicate the importance of regional vulnerability and might aid to identify hot-spot regions for potential climate-triggered violent social conflicts.

Open Source Tools for Seismicity Analysis

NASA Astrophysics Data System (ADS)

Powers, P.

2010-12-01

The spatio-temporal analysis of seismicity plays an important role in earthquake forecasting and is integral to research on earthquake interactions and triggering. For instance, the third version of the Uniform California Earthquake Rupture Forecast (UCERF), currently under development, will use Epidemic Type Aftershock Sequences (ETAS) as a model for earthquake triggering. UCERF will be a "living" model and therefore requires robust, tested, and well-documented ETAS algorithms to ensure transparency and reproducibility. Likewise, as earthquake aftershock sequences unfold, real-time access to high quality hypocenter data makes it possible to monitor the temporal variability of statistical properties such as the parameters of the Omori Law and the Gutenberg Richter b-value. Such statistical properties are valuable as they provide a measure of how much a particular sequence deviates from expected behavior and can be used when assigning probabilities of aftershock occurrence. To address these demands and provide public access to standard methods employed in statistical seismology, we present well-documented, open-source JavaScript and Java software libraries for the on- and off-line analysis of seismicity. The Javascript classes facilitate web-based asynchronous access to earthquake catalog data and provide a framework for in-browser display, analysis, and manipulation of catalog statistics; implementations of this framework will be made available on the USGS Earthquake Hazards website. The Java classes, in addition to providing tools for seismicity analysis, provide tools for modeling seismicity and generating synthetic catalogs. These tools are extensible and will be released as part of the open-source OpenSHA Commons library.

On Statistical Analysis of Neuroimages with Imperfect Registration

PubMed Central

Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

2016-01-01

A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

Evaluation of the prediction precision capability of partial least squares regression approach for analysis of high alloy steel by laser induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Sarkar, Arnab; Karki, Vijay; Aggarwal, Suresh K.; Maurya, Gulab S.; Kumar, Rohit; Rai, Awadhesh K.; Mao, Xianglei; Russo, Richard E.

2015-06-01

Laser induced breakdown spectroscopy (LIBS) was applied for elemental characterization of high alloy steel using partial least squares regression (PLSR) with an objective to evaluate the analytical performance of this multivariate approach. The optimization of the number of principle components for minimizing error in PLSR algorithm was investigated. The effect of different pre-treatment procedures on the raw spectral data before PLSR analysis was evaluated based on several statistical (standard error of prediction, percentage relative error of prediction etc.) parameters. The pre-treatment with "NORM" parameter gave the optimum statistical results. The analytical performance of PLSR model improved by increasing the number of laser pulses accumulated per spectrum as well as by truncating the spectrum to appropriate wavelength region. It was found that the statistical benefit of truncating the spectrum can also be accomplished by increasing the number of laser pulses per accumulation without spectral truncation. The constituents (Co and Mo) present in hundreds of ppm were determined with relative precision of 4-9% (2σ), whereas the major constituents Cr and Ni (present at a few percent levels) were determined with a relative precision of ~ 2%(2σ).

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Spatial Statistics for Tumor Cell Counting and Classification

NASA Astrophysics Data System (ADS)

Wirjadi, Oliver; Kim, Yoo-Jin; Breuel, Thomas

To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.

The Ups and Downs of Repeated Cleavage and Internal Fragment Production in Top-Down Proteomics.

PubMed

Lyon, Yana A; Riggs, Dylan; Fornelli, Luca; Compton, Philip D; Julian, Ryan R

2018-01-01

Analysis of whole proteins by mass spectrometry, or top-down proteomics, has several advantages over methods relying on proteolysis. For example, proteoforms can be unambiguously identified and examined. However, from a gas-phase ion-chemistry perspective, proteins are enormous molecules that present novel challenges relative to peptide analysis. Herein, the statistics of cleaving the peptide backbone multiple times are examined to evaluate the inherent propensity for generating internal versus terminal ions. The raw statistics reveal an inherent bias favoring production of terminal ions, which holds true regardless of protein size. Importantly, even if the full suite of internal ions is generated by statistical dissociation, terminal ions are predicted to account for at least 50% of the total ion current, regardless of protein size, if there are three backbone dissociations or fewer. Top-down analysis should therefore be a viable approach for examining proteins of significant size. Comparison of the purely statistical analysis with actual top-down data derived from ultraviolet photodissociation (UVPD) and higher-energy collisional dissociation (HCD) reveals that terminal ions account for much of the total ion current in both experiments. Terminal ion production is more favored in UVPD relative to HCD, which is likely due to differences in the mechanisms controlling fragmentation. Importantly, internal ions are not found to dominate from either the theoretical or experimental point of view. Graphical abstract ᅟ.

The Ups and Downs of Repeated Cleavage and Internal Fragment Production in Top-Down Proteomics

NASA Astrophysics Data System (ADS)

Lyon, Yana A.; Riggs, Dylan; Fornelli, Luca; Compton, Philip D.; Julian, Ryan R.

2018-01-01

Analysis of whole proteins by mass spectrometry, or top-down proteomics, has several advantages over methods relying on proteolysis. For example, proteoforms can be unambiguously identified and examined. However, from a gas-phase ion-chemistry perspective, proteins are enormous molecules that present novel challenges relative to peptide analysis. Herein, the statistics of cleaving the peptide backbone multiple times are examined to evaluate the inherent propensity for generating internal versus terminal ions. The raw statistics reveal an inherent bias favoring production of terminal ions, which holds true regardless of protein size. Importantly, even if the full suite of internal ions is generated by statistical dissociation, terminal ions are predicted to account for at least 50% of the total ion current, regardless of protein size, if there are three backbone dissociations or fewer. Top-down analysis should therefore be a viable approach for examining proteins of significant size. Comparison of the purely statistical analysis with actual top-down data derived from ultraviolet photodissociation (UVPD) and higher-energy collisional dissociation (HCD) reveals that terminal ions account for much of the total ion current in both experiments. Terminal ion production is more favored in UVPD relative to HCD, which is likely due to differences in the mechanisms controlling fragmentation. Importantly, internal ions are not found to dominate from either the theoretical or experimental point of view. [Figure not available: see fulltext.

Revisiting Information Technology tools serving authorship and editorship: a case-guided tutorial to statistical analysis and plagiarism detection

PubMed Central

Bamidis, P D; Lithari, C; Konstantinidis, S T

2010-01-01

With the number of scientific papers published in journals, conference proceedings, and international literature ever increasing, authors and reviewers are not only facilitated with an abundance of information, but unfortunately continuously confronted with risks associated with the erroneous copy of another's material. In parallel, Information Communication Technology (ICT) tools provide to researchers novel and continuously more effective ways to analyze and present their work. Software tools regarding statistical analysis offer scientists the chance to validate their work and enhance the quality of published papers. Moreover, from the reviewers and the editor's perspective, it is now possible to ensure the (text-content) originality of a scientific article with automated software tools for plagiarism detection. In this paper, we provide a step-bystep demonstration of two categories of tools, namely, statistical analysis and plagiarism detection. The aim is not to come up with a specific tool recommendation, but rather to provide useful guidelines on the proper use and efficiency of either category of tools. In the context of this special issue, this paper offers a useful tutorial to specific problems concerned with scientific writing and review discourse. A specific neuroscience experimental case example is utilized to illustrate the young researcher's statistical analysis burden, while a test scenario is purpose-built using open access journal articles to exemplify the use and comparative outputs of seven plagiarism detection software pieces. PMID:21487489

Data analysis of gravitational-wave signals from spinning neutron stars. III. Detection statistics and computational requirements

NASA Astrophysics Data System (ADS)

Jaranowski, Piotr; Królak, Andrzej

2000-03-01

We develop the analytic and numerical tools for data analysis of the continuous gravitational-wave signals from spinning neutron stars for ground-based laser interferometric detectors. The statistical data analysis method that we investigate is maximum likelihood detection which for the case of Gaussian noise reduces to matched filtering. We study in detail the statistical properties of the optimum functional that needs to be calculated in order to detect the gravitational-wave signal and estimate its parameters. We find it particularly useful to divide the parameter space into elementary cells such that the values of the optimal functional are statistically independent in different cells. We derive formulas for false alarm and detection probabilities both for the optimal and the suboptimal filters. We assess the computational requirements needed to do the signal search. We compare a number of criteria to build sufficiently accurate templates for our data analysis scheme. We verify the validity of our concepts and formulas by means of the Monte Carlo simulations. We present algorithms by which one can estimate the parameters of the continuous signals accurately. We find, confirming earlier work of other authors, that given a 100 Gflops computational power an all-sky search for observation time of 7 days and directed search for observation time of 120 days are possible whereas an all-sky search for 120 days of observation time is computationally prohibitive.

Revisiting Information Technology tools serving authorship and editorship: a case-guided tutorial to statistical analysis and plagiarism detection.

PubMed

Bamidis, P D; Lithari, C; Konstantinidis, S T

2010-12-01

With the number of scientific papers published in journals, conference proceedings, and international literature ever increasing, authors and reviewers are not only facilitated with an abundance of information, but unfortunately continuously confronted with risks associated with the erroneous copy of another's material. In parallel, Information Communication Technology (ICT) tools provide to researchers novel and continuously more effective ways to analyze and present their work. Software tools regarding statistical analysis offer scientists the chance to validate their work and enhance the quality of published papers. Moreover, from the reviewers and the editor's perspective, it is now possible to ensure the (text-content) originality of a scientific article with automated software tools for plagiarism detection. In this paper, we provide a step-bystep demonstration of two categories of tools, namely, statistical analysis and plagiarism detection. The aim is not to come up with a specific tool recommendation, but rather to provide useful guidelines on the proper use and efficiency of either category of tools. In the context of this special issue, this paper offers a useful tutorial to specific problems concerned with scientific writing and review discourse. A specific neuroscience experimental case example is utilized to illustrate the young researcher's statistical analysis burden, while a test scenario is purpose-built using open access journal articles to exemplify the use and comparative outputs of seven plagiarism detection software pieces.

Statistical science: a grammar for research.

PubMed

Cox, David R

2017-06-01

I greatly appreciate the invitation to give this lecture with its century long history. The title is a warning that the lecture is rather discursive and not highly focused and technical. The theme is simple. That statistical thinking provides a unifying set of general ideas and specific methods relevant whenever appreciable natural variation is present. To be most fruitful these ideas should merge seamlessly with subject-matter considerations. By contrast, there is sometimes a temptation to regard formal statistical analysis as a ritual to be added after the serious work has been done, a ritual to satisfy convention, referees, and regulatory agencies. I want implicitly to refute that idea.

Automatic identification of bacterial types using statistical imaging methods

NASA Astrophysics Data System (ADS)

Trattner, Sigal; Greenspan, Hayit; Tepper, Gapi; Abboud, Shimon

2003-05-01

The objective of the current study is to develop an automatic tool to identify bacterial types using computer-vision and statistical modeling techniques. Bacteriophage (phage)-typing methods are used to identify and extract representative profiles of bacterial types, such as the Staphylococcus Aureus. Current systems rely on the subjective reading of plaque profiles by human expert. This process is time-consuming and prone to errors, especially as technology is enabling the increase in the number of phages used for typing. The statistical methodology presented in this work, provides for an automated, objective and robust analysis of visual data, along with the ability to cope with increasing data volumes.

Rule-based statistical data mining agents for an e-commerce application

NASA Astrophysics Data System (ADS)

Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

2003-03-01

Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

Investigation of Pre-Earthquake Ionospheric Disturbances by 3D Tomographic Analysis

NASA Astrophysics Data System (ADS)

Yagmur, M.

2016-12-01

Ionospheric variations before earthquakes have been widely discussed phenomena in ionospheric studies. To clarify the source and mechanism of these phenomena is highly important for earthquake forecasting. To well understanding the mechanical and physical processes of pre-seismic Ionospheric anomalies that might be related even with Lithosphere-Atmosphere-Ionosphere-Magnetosphere Coupling, both statistical and 3D modeling analysis are needed. For these purpose, firstly we have investigated the relation between Ionospheric TEC Anomalies and potential source mechanisms such as space weather activity and lithospheric phenomena like positive surface electric charges. To distinguish their effects on Ionospheric TEC, we have focused on pre-seismically active days. Then, we analyzed the statistical data of 54 earthquakes that M≽6 between 2000 and 2013 as well as the 2011 Tohoku and the 2016 Kumamoto Earthquakes in Japan. By comparing TEC anomaly and Solar activity by Dst Index, we have found that 28 events that might be related with Earthquake activity. Following the statistical analysis, we also investigate the Lithospheric effect on TEC change on selected days. Among those days, we have chosen two case studies as the 2011 Tohoku and the 2016 Kumamoto Earthquakes to make 3D reconstructed images by utilizing 3D Tomography technique with Neural Networks. The results will be presented in our presentation. Keywords : Earthquake, 3D Ionospheric Tomography, Positive and Negative Anomaly, Geomagnetic Storm, Lithosphere

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

What is too much variation? The null hypothesis in small-area analysis.

PubMed Central

Diehr, P; Cain, K; Connell, F; Volinn, E

1990-01-01

A small-area analysis (SAA) in health services research often calculates surgery rates for several small areas, compares the largest rate to the smallest, notes that the difference is large, and attempts to explain this discrepancy as a function of service availability, physician practice styles, or other factors. SAAs are often difficult to interpret because there is little theoretical basis for determining how much variation would be expected under the null hypothesis that all of the small areas have similar underlying surgery rates and that the observed variation is due to chance. We developed a computer program to simulate the distribution of several commonly used descriptive statistics under the null hypothesis, and used it to examine the variability in rates among the counties of the state of Washington. The expected variability when the null hypothesis is true is surprisingly large, and becomes worse for procedures with low incidence, for smaller populations, when there is variability among the populations of the counties, and when readmissions are possible. The characteristics of four descriptive statistics were studied and compared. None was uniformly good, but the chi-square statistic had better performance than the others. When we reanalyzed five journal articles that presented sufficient data, the results were usually statistically significant. Since SAA research today is tending to deal with low-incidence events, smaller populations, and measures where readmissions are possible, more research is needed on the distribution of small-area statistics under the null hypothesis. New standards are proposed for the presentation of SAA results. PMID:2312306

What is too much variation? The null hypothesis in small-area analysis.

PubMed

Diehr, P; Cain, K; Connell, F; Volinn, E

1990-02-01

A small-area analysis (SAA) in health services research often calculates surgery rates for several small areas, compares the largest rate to the smallest, notes that the difference is large, and attempts to explain this discrepancy as a function of service availability, physician practice styles, or other factors. SAAs are often difficult to interpret because there is little theoretical basis for determining how much variation would be expected under the null hypothesis that all of the small areas have similar underlying surgery rates and that the observed variation is due to chance. We developed a computer program to simulate the distribution of several commonly used descriptive statistics under the null hypothesis, and used it to examine the variability in rates among the counties of the state of Washington. The expected variability when the null hypothesis is true is surprisingly large, and becomes worse for procedures with low incidence, for smaller populations, when there is variability among the populations of the counties, and when readmissions are possible. The characteristics of four descriptive statistics were studied and compared. None was uniformly good, but the chi-square statistic had better performance than the others. When we reanalyzed five journal articles that presented sufficient data, the results were usually statistically significant. Since SAA research today is tending to deal with low-incidence events, smaller populations, and measures where readmissions are possible, more research is needed on the distribution of small-area statistics under the null hypothesis. New standards are proposed for the presentation of SAA results.

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Feature-Based Statistical Analysis of Combustion Simulation Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, J; Krishnamoorthy, V; Liu, S

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 andmore » 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 science; however, it is applicable to many other science domains.« less

Statistical assessment of bi-exponential diffusion weighted imaging signal characteristics induced by intravoxel incoherent motion in malignant breast tumors

PubMed Central

Wong, Oi Lei; Lo, Gladys G.; Chan, Helen H. L.; Wong, Ting Ting; Cheung, Polly S. Y.

2016-01-01

Background The purpose of this study is to statistically assess whether bi-exponential intravoxel incoherent motion (IVIM) model better characterizes diffusion weighted imaging (DWI) signal of malignant breast tumor than mono-exponential Gaussian diffusion model. Methods 3 T DWI data of 29 malignant breast tumors were retrospectively included. Linear least-square mono-exponential fitting and segmented least-square bi-exponential fitting were used for apparent diffusion coefficient (ADC) and IVIM parameter quantification, respectively. F-test and Akaike Information Criterion (AIC) were used to statistically assess the preference of mono-exponential and bi-exponential model using region-of-interests (ROI)-averaged and voxel-wise analysis. Results For ROI-averaged analysis, 15 tumors were significantly better fitted by bi-exponential function and 14 tumors exhibited mono-exponential behavior. The calculated ADC, D (true diffusion coefficient) and f (pseudo-diffusion fraction) showed no significant differences between mono-exponential and bi-exponential preferable tumors. Voxel-wise analysis revealed that 27 tumors contained more voxels exhibiting mono-exponential DWI decay while only 2 tumors presented more bi-exponential decay voxels. ADC was consistently and significantly larger than D for both ROI-averaged and voxel-wise analysis. Conclusions Although the presence of IVIM effect in malignant breast tumors could be suggested, statistical assessment shows that bi-exponential fitting does not necessarily better represent the DWI signal decay in breast cancer under clinically typical acquisition protocol and signal-to-noise ratio (SNR). Our study indicates the importance to statistically examine the breast cancer DWI signal characteristics in practice. PMID:27709078

Role of diversity in ICA and IVA: theory and applications

NASA Astrophysics Data System (ADS)

Adalı, Tülay

2016-05-01

Independent component analysis (ICA) has been the most popular approach for solving the blind source separation problem. Starting from a simple linear mixing model and the assumption of statistical independence, ICA can recover a set of linearly-mixed sources to within a scaling and permutation ambiguity. It has been successfully applied to numerous data analysis problems in areas as diverse as biomedicine, communications, finance, geo- physics, and remote sensing. ICA can be achieved using different types of diversity—statistical property—and, can be posed to simultaneously account for multiple types of diversity such as higher-order-statistics, sample dependence, non-circularity, and nonstationarity. A recent generalization of ICA, independent vector analysis (IVA), generalizes ICA to multiple data sets and adds the use of one more type of diversity, statistical dependence across the data sets, for jointly achieving independent decomposition of multiple data sets. With the addition of each new diversity type, identification of a broader class of signals become possible, and in the case of IVA, this includes sources that are independent and identically distributed Gaussians. We review the fundamentals and properties of ICA and IVA when multiple types of diversity are taken into account, and then ask the question whether diversity plays an important role in practical applications as well. Examples from various domains are presented to demonstrate that in many scenarios it might be worthwhile to jointly account for multiple statistical properties. This paper is submitted in conjunction with the talk delivered for the "Unsupervised Learning and ICA Pioneer Award" at the 2016 SPIE Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications.

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

PubMed

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

Local statistics of retinal optic flow for self-motion through natural sceneries.

PubMed

Calow, Dirk; Lappe, Markus

2007-12-01

Image analysis in the visual system is well adapted to the statistics of natural scenes. Investigations of natural image statistics have so far mainly focused on static features. The present study is dedicated to the measurement and the analysis of the statistics of optic flow generated on the retina during locomotion through natural environments. Natural locomotion includes bouncing and swaying of the head and eye movement reflexes that stabilize gaze onto interesting objects in the scene while walking. We investigate the dependencies of the local statistics of optic flow on the depth structure of the natural environment and on the ego-motion parameters. To measure these dependencies we estimate the mutual information between correlated data sets. We analyze the results with respect to the variation of the dependencies over the visual field, since the visual motions in the optic flow vary depending on visual field position. We find that retinal flow direction and retinal speed show only minor statistical interdependencies. Retinal speed is statistically tightly connected to the depth structure of the scene. Retinal flow direction is statistically mostly driven by the relation between the direction of gaze and the direction of ego-motion. These dependencies differ at different visual field positions such that certain areas of the visual field provide more information about ego-motion and other areas provide more information about depth. The statistical properties of natural optic flow may be used to tune the performance of artificial vision systems based on human imitating behavior, and may be useful for analyzing properties of natural vision systems.

Thirty Meter Telescope Site Testing V: Seeing and Isoplanatic Angle

NASA Astrophysics Data System (ADS)

Skidmore, Warren; Els, Sebastian; Travouillon, Tony; Riddle, Reed; Schöck, Matthias; Bustos, Edison; Seguel, Juan; Walker, David

2009-10-01

In this article we present an analysis of the statistical and temporal properties of seeing and isoplanatic angle measurements obtained with combined Differential Image Motion Monitor (DIMM) and Multi-Aperture Scintillation Sensor (MASS) units at the Thirty Meter Telescope (TMT) candidate sites. For each of the five candidate sites we obtained multiyear, high-cadence, high-quality seeing measurements. These data allow for a broad and detailed analysis, giving us a good understanding of the characteristics of each of the sites. The overall seeing statistics for the five candidate sites are presented, broken into total seeing (measured by the DIMM), free-atmosphere seeing and isoplanatic angle (measured by the MASS), and ground-layer seeing (difference between the total and free-atmosphere seeing). We examine the statistical distributions of seeing measurements and investigate annual and nightly behavior. The properties of the seeing measurements are discussed in terms of the geography and meteorological conditions at each site. The temporal variability of the seeing measurements over timescales of minutes to hours is derived for each site. We find that each of the TMT candidate sites has its own strengths and weaknesses when compared against the other candidate sites. The results presented in this article form part of the full set of results that are used for the TMT site-selection process. This is the fifth article in a series discussing the TMT site-testing project.

Statistical analysis of modeling error in structural dynamic systems

NASA Technical Reports Server (NTRS)

Hasselman, T. K.; Chrostowski, J. D.

1990-01-01

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Modeling of the reactant conversion rate in a turbulent shear flow

NASA Technical Reports Server (NTRS)

Frankel, S. H.; Madnia, C. K.; Givi, P.

1992-01-01

Results are presented of direct numerical simulations (DNS) of spatially developing shear flows under the influence of infinitely fast chemical reactions of the type A + B yields Products. The simulation results are used to construct the compositional structure of the scalar field in a statistical manner. The results of this statistical analysis indicate that the use of a Beta density for the probability density function (PDF) of an appropriate Shvab-Zeldovich mixture fraction provides a very good estimate of the limiting bounds of the reactant conversion rate within the shear layer. This provides a strong justification for the implementation of this density in practical modeling of non-homogeneous turbulent reacting flows. However, the validity of the model cannot be generalized for predictions of higher order statistical quantities. A closed form analytical expression is presented for predicting the maximum rate of reactant conversion in non-homogeneous reacting turbulence.

Statistical Analysis of Research Data | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

PubMed

Shaikh, Masood Ali

2017-09-01

Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.

Parallel processing of genomics data

NASA Astrophysics Data System (ADS)

Agapito, Giuseppe; Guzzi, Pietro Hiram; Cannataro, Mario

2016-10-01

The availability of high-throughput experimental platforms for the analysis of biological samples, such as mass spectrometry, microarrays and Next Generation Sequencing, have made possible to analyze a whole genome in a single experiment. Such platforms produce an enormous volume of data per single experiment, thus the analysis of this enormous flow of data poses several challenges in term of data storage, preprocessing, and analysis. To face those issues, efficient, possibly parallel, bioinformatics software needs to be used to preprocess and analyze data, for instance to highlight genetic variation associated with complex diseases. In this paper we present a parallel algorithm for the parallel preprocessing and statistical analysis of genomics data, able to face high dimension of data and resulting in good response time. The proposed system is able to find statistically significant biological markers able to discriminate classes of patients that respond to drugs in different ways. Experiments performed on real and synthetic genomic datasets show good speed-up and scalability.

Analysis of the sleep quality of elderly people using biomedical signals.

PubMed

Moreno-Alsasua, L; Garcia-Zapirain, B; Mendez-Zorrilla, A

2015-01-01

This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the level of a person's rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

Reconnection properties in Kelvin-Helmholtz instabilities

NASA Astrophysics Data System (ADS)

Vernisse, Y.; Lavraud, B.; Eriksson, S.; Gershman, D. J.; Dorelli, J.; Pollock, C. J.; Giles, B. L.; Aunai, N.; Avanov, L. A.; Burch, J.; Chandler, M. O.; Coffey, V. N.; Dargent, J.; Ergun, R.; Farrugia, C. J.; Genot, V. N.; Graham, D.; Hasegawa, H.; Jacquey, C.; Kacem, I.; Khotyaintsev, Y. V.; Li, W.; Magnes, W.; Marchaudon, A.; Moore, T. E.; Paterson, W. R.; Penou, E.; Phan, T.; Retino, A.; Schwartz, S. J.; Saito, Y.; Sauvaud, J. A.; Schiff, C.; Torbert, R. B.; Wilder, F. D.; Yokota, S.

2017-12-01

Kelvin-Helmholtz instabilities are particular laboratories to study strong guide field reconnection processes. In particular, unlike the usual dayside magnetopause, the conditions across the magnetopause in KH vortices are quasi-symmetric, with low differences in beta and magnetic shear angle. We study these properties by means of statistical analysis of the high-resolution data of the Magnetospheric Multiscale mission. Several events of Kelvin-Helmholtz instabilities pas the terminator plane and a long lasting dayside instabilities event where used in order to produce this statistical analysis. Early results present a consistency between the data and the theory. In addition, the results emphasize the importance of the thickness of the magnetopause as a driver of magnetic reconnection in low magnetic shear events.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

System of Mueller-Jones matrix polarizing mapping of blood plasma films in breast pathology

NASA Astrophysics Data System (ADS)

Zabolotna, Natalia I.; Radchenko, Kostiantyn O.; Tarnovskiy, Mykola H.

2017-08-01

The combined method of Jones-Mueller matrix mapping and blood plasma films analysis based on the system that proposed in this paper. Based on the obtained data about the structure and state of blood plasma samples the diagnostic conclusions can be make about the state of breast cancer patients ("normal" or "pathology"). Then, by using the statistical analysis obtain statistical and correlational moments for every coordinate distributions; these indicators are served as diagnostic criterias. The final step is to comparing results and choosing the most effective diagnostic indicators. The paper presents the results of Mueller-Jones matrix mapping of optically thin (attenuation coefficient ,τ≤0,1) blood plasma layers.

Getting the big picture in community science: methods that capture context.

PubMed

Luke, Douglas A

2005-06-01

Community science has a rich tradition of using theories and research designs that are consistent with its core value of contextualism. However, a survey of empirical articles published in the American Journal of Community Psychology shows that community scientists utilize a narrow range of statistical tools that are not well suited to assess contextual data. Multilevel modeling, geographic information systems (GIS), social network analysis, and cluster analysis are recommended as useful tools to address contextual questions in community science. An argument for increased methodological consilience is presented, where community scientists are encouraged to adopt statistical methodology that is capable of modeling a greater proportion of the data than is typical with traditional methods.

Thou Shalt Be Reproducible! A Technology Perspective

PubMed Central

Mair, Patrick

2016-01-01

This article elaborates on reproducibility in psychology from a technological viewpoint. Modern open source computational environments are shown and explained that foster reproducibility throughout the whole research life cycle, and to which emerging psychology researchers should be sensitized, are shown and explained. First, data archiving platforms that make datasets publicly available are presented. Second, R is advocated as the data-analytic lingua franca in psychology for achieving reproducible statistical analysis. Third, dynamic report generation environments for writing reproducible manuscripts that integrate text, data analysis, and statistical outputs such as figures and tables in a single document are described. Supplementary materials are provided in order to get the reader started with these technologies. PMID:27471486

An analysis of Minnesota's fifth forest resources inventory, 1990.

Treesearch

Earl C. Leatherberry; John S. Jr. Spencer; Thomas L. Schmidt; Michael R. Carroll

1995-01-01

The fifth Minnesota forest inventory found 16.7 million acres of forest land in 1990, of which 14.7 million acres is timberland. Growing-stock volume on timberland increased from 12.4 to 15.1 billion cubic feet between 1977 and 1990, a gain of 22%. Analysis and statistics on forest area, timber volume, growth, removals, mortality, and projections are presented.

Vermont's use-value appraisal property tax program: a forest inventory and analysis

Treesearch

Paul E. Sendak; Donald F. Dennis; Donald F. Dennis

1989-01-01

A statistical report and analysis of the timberland enrolled in the Vermont Use Value Appraisal (UVA) property tax program. The study was conducted using data collected in the fourth forest survey of Vermont (1983). Estimates are presented on land area, timber volumes, tree quality, numbers of live trees, and biomass for timberland enrolled in the UVA program and for...