November 26, 2020

Download Ebook Free Chi-Squared Goodness Of Fit Tests With Applications

Chi-Squared Goodness of Fit Tests with Applications

Chi-Squared Goodness of Fit Tests with Applications
Author : N. Balakrishnan,Vassilly Voinov,M.S Nikulin
Publisher : Academic Press
Release Date : 2013-01-25
Category : Mathematics
Total pages :256
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Chi-Squared Goodness of Fit Tests with Applications provides a thorough and complete context for the theoretical basis and implementation of Pearson’s monumental contribution and its wide applicability for chi-squared goodness of fit tests. The book is ideal for researchers and scientists conducting statistical analysis in processing of experimental data as well as to students and practitioners with a good mathematical background who use statistical methods. The historical context, especially Chapter 7, provides great insight into importance of this subject with an authoritative author team. This reference includes the most recent application developments in using these methods and models. Systematic presentation with interesting historical context and coverage of the fundamentals of the subject Presents modern model validity methods, graphical techniques, and computer-intensive methods Recent research and a variety of open problems Interesting real-life examples for practitioners

Chi-squared Goodness of Fit Tests with Applications

Chi-squared Goodness of Fit Tests with Applications
Author : Vassiliy Voinov,N. Balakrishnan,Mikhail Stepanovich Nikulin
Publisher : Unknown
Release Date : 2013
Category : Mathematics
Total pages :229
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"If the number of sample observations n ! 1, the statistic in (1.1) will follow the chi-squared probability distribution with r-1 degrees of freedom. We know that this remarkable result is true only for a simple null hypothesis when a hypothetical distribution is specified uniquely (i.e., the parameter is considered to be known). Until 1934, Pearson believed that the limiting distribution of the statistic in (1.1) will be the same if the unknown parameters of the null hypothesis are replaced by their estimates based on a sample; see, for example, Baird (1983), Plackett (1983, p. 63), Lindley (1996), Rao (2002), and Stigler (2008, p. 266). In this regard, it is important to reproduce the words of Plackett (1983, p. 69) concerning E. S. Pearson's opinion: "I knew long ago that KP (meaning Karl Pearson) used the 'correct' degrees of freedom for (a) difference between two samples and (b) multiple contingency tables. But he could not see that

Chi-squared Goodness-of-fit Tests for Censored Data

Chi-squared Goodness-of-fit Tests for Censored Data
Author : Mikhail S. Nikulin,Ekaterina V. Chimitova
Publisher : John Wiley & Sons
Release Date : 2017-06-29
Category : Mathematics
Total pages :158
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This book is devoted to the problems of construction and application of chi-squared goodness-of-fit tests for complete and censored data. Classical chi-squared tests assume that unknown distribution parameters are estimated using grouped data, but in practice this assumption is often forgotten. In this book, we consider modified chi-squared tests, which do not suffer from such a drawback. The authors provide examples of chi-squared tests for various distributions widely used in practice, and also consider chi-squared tests for the parametric proportional hazards model and accelerated failure time model, which are widely used in reliability and survival analysis. Particular attention is paid to the choice of grouping intervals and simulations. This book covers recent innovations in the field as well as important results previously only published in Russian. Chi-squared tests are compared with other goodness-of-fit tests (such as the Cramer-von Mises-Smirnov, Anderson-Darling and Zhang tests) in terms of power when testing close competing hypotheses.

Asymptotics for Generalized Chi-square Goodness-of-fit Tests

Asymptotics for Generalized Chi-square Goodness-of-fit Tests
Author : Feike C. Drost
Publisher : Unknown
Release Date : 1988
Category : Asymptotic distribution (Probability theory)
Total pages :104
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Goodness-of-Fit Tests and Model Validity

Goodness-of-Fit Tests and Model Validity
Author : C. Huber-Carol,N. Balakrishnan,M. Nikulin,M. Mesbah
Publisher : Springer Science & Business Media
Release Date : 2012-12-06
Category : Mathematics
Total pages :507
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The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.

Econometric Advances in Spatial Modelling and Methodology

Econometric Advances in Spatial Modelling and Methodology
Author : Daniel A. Griffith,C. Amrhein,Jean-Marie Huriót
Publisher : Springer Science & Business Media
Release Date : 1998-03-31
Category : Business & Economics
Total pages :196
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The purpose of models is not to fit the data but to sharpen the questions. S. Karlin, 11th R. A. Fisher Memorial Lecture, Royal Society, 20 April 1983 We are proud to offer this volume in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Not one to model solely for the sake of modelling, the above quotation nicely captures Professor Paelinck's unceasing quest for the best question for which an answer is needed. His FLEUR model has sharpened many spatial economics and spatial econometrics questions! Jean Paelinck, arguably, is the founder of modem spatial econometrics, penning the seminal introductory monograph on this topic, Spatial Econometrics, with Klaassen in 1979. In the General Address to the Dutch Statistical Association, on May 2, 1974, in Tilburg, "he coined the term [spatial econometrics] to designate a growing body of the regional science literature that dealt primarily with estimation and testing problems encountered in the implementation of multiregional econometric models" (Anselin, 1988, p. 7); he already had introduced this idea in his introductory report to the 1966 Annual Meeting of the Association de Science Regionale de Langue Fran~aise.

A Guide to Chi-Squared Testing

A Guide to Chi-Squared Testing
Author : Priscilla E. Greenwood,Michael S. Nikulin
Publisher : John Wiley & Sons
Release Date : 1996-04-05
Category : Mathematics
Total pages :304
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The first step-by-step guide to conducting successful Chi-squaredtests Chi-squared testing is one of the most commonly applied statisticaltechniques. It provides reliable answers for researchers in a widerange of fields, including engineering, manufacturing, finance,agriculture, and medicine. A Guide to Chi-Squared Testing brings readers up to date on recentinnovations and important material previously published only in theformer Soviet Union. Its clear, concise treatment and practicaladvice make this an ideal reference for all researchers andconsultants. Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstratethe application of these general purpose tests in a wide variety ofspecific settings. They also * Detail the various decisions to be made when applying Chi-squaredtests to real data, and the proper application of these tests instandard hypothesis-testing situations * Describe how Chi-squared type tests allow statisticians toconstruct a test statistic whose distribution is asymptoticallyChi-squared, and to compute power against various alternatives * Devote half of the book to examples of Chi-squared tests that canbe easily adapted to situations not covered in the book * Provide a self-contained, accessible treatment of themathematical requisites * Include an extensive bibliography and suggestions for furtherreading

An Introduction to Statistical Analysis in Research

An Introduction to Statistical Analysis in Research
Author : Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Pablo F. Weaver,Kanya Godde
Publisher : John Wiley & Sons
Release Date : 2017-09-05
Category : Mathematics
Total pages :616
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Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.

OpenIntro Statistics

OpenIntro Statistics
Author : David Diez,Christopher Barr,Mine Çetinkaya-Rundel
Publisher : Unknown
Release Date : 2015-07-02
Category :
Total pages :129
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The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Goodness-of-Fit-Techniques

Goodness-of-Fit-Techniques
Author : Ralph B. D'Agostino
Publisher : CRC Press
Release Date : 1986-06-02
Category : Mathematics
Total pages :576
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Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction, and also collecting methods of testing for specific famous distributions, this useful reference is the first comprehensive review of the extensive literature on the subject. It surveysthe leading methods of testing fit . .. provides tables to make the tests available . .. assessesthe comparative merits of different test procedures . .. and supplies numerical examples to aidin understanding these techniques.Goodness-of-Fit Techniques shows how to apply the techniques . .. emphasizes testing for thethree major distributions, normal, exponential, and uniform . .. discusses the handling of censoreddata .. . and contains over 650 bibliographic citations that cover the field.Illustrated with tables and drawings, this volume is an ideal reference for mathematical andapplied statisticians, and biostatisticians; professionals in applied science fields, including psychologists, biometricians, physicians, and quality control and reliability engineers; advancedundergraduate- and graduate-level courses on goodness-of-fit techniques; and professional seminarsand symposia on applied statistics, quality control, and reliability.

Goodness-of-Fit Statistics for Discrete Multivariate Data

Goodness-of-Fit Statistics for Discrete Multivariate Data
Author : Timothy R.C. Read,Noel A.C. Cressie
Publisher : Springer Science & Business Media
Release Date : 2012-12-06
Category : Mathematics
Total pages :212
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The statistical analysis of discrete multivariate data has received a great deal of attention in the statistics literature over the past two decades. The develop ment ofappropriate models is the common theme of books such as Cox (1970), Haberman (1974, 1978, 1979), Bishop et al. (1975), Gokhale and Kullback (1978), Upton (1978), Fienberg (1980), Plackett (1981), Agresti (1984), Goodman (1984), and Freeman (1987). The objective of our book differs from those listed above. Rather than concentrating on model building, our intention is to describe and assess the goodness-of-fit statistics used in the model verification part of the inference process. Those books that emphasize model development tend to assume that the model can be tested with one of the traditional goodness-of-fit tests 2 2 (e.g., Pearson's X or the loglikelihood ratio G ) using a chi-squared critical value. However, it is well known that this can give a poor approximation in many circumstances. This book provides the reader with a unified analysis of the traditional goodness-of-fit tests, describing their behavior and relative merits as well as introducing some new test statistics. The power-divergence family of statistics (Cressie and Read, 1984) is used to link the traditional test statistics through a single real-valued parameter, and provides a way to consolidate and extend the current fragmented literature. As a by-product of our analysis, a new 2 2 statistic emerges "between" Pearson's X and the loglikelihood ratio G that has some valuable properties.

Encyclopedia of Research Design

Encyclopedia of Research Design
Author : Neil J. Salkind
Publisher : SAGE
Release Date : 2010-06-22
Category : Philosophy
Total pages :1776
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"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Encyclopedia of Epidemiology

Encyclopedia of Epidemiology
Author : Sarah Boslaugh,Louise-Anne McNutt
Publisher : SAGE
Release Date : 2008
Category : Medical
Total pages :1111
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The Encyclopedia of Epidemiology presents state-of-the-art information from the field of epidemiology in a less technical and accessible style and format. With more than 600 entries, no single reference provides as comprehensive a resource in as focused and appropriate manner. The entries cover every major facet of epidemiology, from risk ratios to case-control studies to mediating and moderating variables, and much more. Relevant topics from related fields such as biostatistics and health economics are also included.

The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation

The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation
Author : Bruce B. Frey
Publisher : SAGE Publications
Release Date : 2018-01-29
Category : Education
Total pages :2000
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In an era of curricular changes and experiments and high-stakes testing, educational measurement and evaluation is more important than ever. In addition to expected entries covering the basics of traditional theories and methods, other entries discuss important sociopolitical issues and trends influencing the future of that research and practice. Textbooks, handbooks, monographs and other publications focus on various aspects of educational research, measurement and evaluation, but to date, there exists no major reference guide for students new to the field. This comprehensive work fills that gap, covering traditional areas while pointing the way to future developments. Features: Nearly 700 signed entries are contained in an authoritative work spanning four volumes and available in choice of electronic and/or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of education research, measurement, and evaluation to more easily locate directly related entries. (For instance, sample themes include Data, Evaluation, Measurement Concepts & Issues, Research, Sociopolitical Issues, Standards.) Back matter includes a Chronology of the development of the field; a Resource Guide to classic books, journals, and associations; and a detailed Index. Entries conclude with References/Further Readings and Cross References to related entries. The Index, Reader’s Guide themes, and Cross References will combine to provide robust search-and-browse in the e-version.

Statistical Techniques for Transportation Engineering

Statistical Techniques for Transportation Engineering
Author : Kumar Molugaram,G Shanker Rao
Publisher : Butterworth-Heinemann
Release Date : 2017-03-03
Category : Technology & Engineering
Total pages :554
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Statistical Techniques for Transportation Engineering is written with a systematic approach in mind and covers a full range of data analysis topics, from the introductory level (basic probability, measures of dispersion, random variable, discrete and continuous distributions) through more generally used techniques (common statistical distributions, hypothesis testing), to advanced analysis and statistical modeling techniques (regression, AnoVa, and time series). The book also provides worked out examples and solved problems for a wide variety of transportation engineering challenges. Demonstrates how to effectively interpret, summarize, and report transportation data using appropriate statistical descriptors Teaches how to identify and apply appropriate analysis methods for transportation data Explains how to evaluate transportation proposals and schemes with statistical rigor