A Contingency Table Approach To Nonparametric Testing
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A Contingency Table Approach to Nonparametric Testing by J.C.W. Rayner,D.J. Best Pdf
Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effects are virtually ignored. Using a fresh approach, A Contingency Table Approach to Nonparametric Testing unifies and extends the popular, standard test
Nonparametric Statistics for Non-Statisticians by Gregory W. Corder,Dale I. Foreman Pdf
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS® screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to: Test data for normality and randomness Use the Wilcoxon signed rank test to compare two related samples Apply the Mann-Whitney U test to compare two unrelated samples Compare more than two related samples using the Friedman test Employ the Kruskal-Wallis H test to compare more than two unrelated samples Compare variables of ordinal or dichotomous scales Test for nominal scale data A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS®, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
Nonparametric Statistical Tests by Markus Neuhauser Pdf
Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th
Practical Nonparametric Statistics by W. J. Conover Pdf
This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures. This edition features some procedures that have withstood the test of time and are now used by many practitioners, such as the Fisher Exact Test for two-by-two contingency tables, the Mantel-Haenszel Test for combining several contingency tables, the Kaplan-Meier estimates of the survival curve, the Jonckheere-Terpstra Test and the Page Test for ordered alternatives, and a discussion of the bootstrap method.
Some introductory concepts; Tests for two independent samples - ordinal or two category response variable;Tests for one sample of two related samples; Tests for several independent samples - categorical explanatory variable; Tests for several independent samples - both variables ordinal; Tests for several related samples - categorical explanatory variable; Tests for several related samples - both variables ordinal; Tests for one sample or several independent samples - both variables categoriacal.
Applied Nonparametric Statistical Methods by Peter Sprent,Nigel C. Smeeton Pdf
While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material, this edition begins with a brief summary of some
Applied Nonparametric Statistics by Wayne W. Daniel Pdf
This book covers the most commonly used nonparametric statistical techniques by emphasizing applications rather than theory. Exercises and examples are drawn from various disciplines including agriculture, biology, sociology, education, psychology, medicine, business, geology, and anthropology. The applications of techniques are presented in a step-by-step format that is repeated for all illustrative examples. Concepts are reinforced with many references to statistical literature to show the relevance to real-world problems. Chapters contain references of available computer programs and software packages that apply to methods presented in the book.
Author : J. C. W. Rayner,G. C. Livingston, Jr. Publisher : John Wiley & Sons Page : 245 pages File Size : 40,7 Mb Release : 2023-02-16 Category : Mathematics ISBN : 9781119832003
An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA by J. C. W. Rayner,G. C. Livingston, Jr. Pdf
An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA Complete reference for applied statisticians and data analysts that uniquely covers the new statistical methodologies that enable deeper data analysis An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA provides readers with powerful new statistical methodologies that enable deeper data analysis. The book offers applied statisticians an introduction to the latest topics in nonparametrics. The worked examples with supporting R code provide analysts the tools they need to apply these methods to their own problems. Co-authored by an internationally recognised expert in the field and an early career researcher with broad skills including data analysis and R programming, the book discusses key topics such as: NP ANOVA methodology Cochran-Mantel-Haenszel (CMH) methodology and design Latin squares and balanced incomplete block designs Parametric ANOVA F tests for continuous data Nonparametric rank tests (the Kruskal-Wallis and Friedman tests) CMH MS tests for the nonparametric analysis of categorical response data Applied statisticians and data analysts, as well as students and professors in data analysis, can use this book to gain a complete understanding of the modern statistical methodologies that are allowing for deeper data analysis.
Applied Nonparametric Statistical Methods, Fourth Edition by Peter Sprent,Nigel C. Smeeton Pdf
While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material, this edition begins with a brief summary of some relevant general statistical concepts and an introduction to basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are now the focus of an entire chapter. The text also expands coverage on the analysis of survival data and the bootstrap method. The new final chapter focuses on important modern developments, such as large sample methods and computer-intensive applications. Keeping mathematics to a minimum, this text introduces nonparametric methods to undergraduate students who are taking either mainstream statistics courses or statistics courses within other disciplines. By giving the proper attention to data collection and the interpretation of analyses, it provides a full introduction to nonparametric methods.
Nonparametric Statistics by Gregory W. Corder,Dale I. Foreman Pdf
“…a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." –CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS® (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures Data sets and odd-numbered solutions provided in an appendix, and tables of critical values Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.
Practical Nonparametric Statistics 3Rd Ed by Conover Pdf
This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures. This edition features some procedures that have withstood the test of time and are now used by many practitioners, such as the Fisher Exact Test for two-by-two contingency tables, the Mantel-Haenszel Test for combining several contingency tables, the Kaplan-Meier estimates of the survival curve, the Jonckheere-Terpstra Test and the Page Test for ordered alternatives, and a discussion of the bootstrap method.· Probability Theory· Statistical Inference· Some Tests Based on the Binomial Distribution· Contingency Tables· Some Methods Based on Ranks· Statistics of the Kolmogorov-Smirnov Type
J. C. W. Rayner,D. J. Best,Per Bruun Brockhoff,G. D. Rayner
Author : J. C. W. Rayner,D. J. Best,Per Bruun Brockhoff,G. D. Rayner Publisher : John Wiley & Sons Page : 191 pages File Size : 40,5 Mb Release : 2016-04-22 Category : Technology & Engineering ISBN : 9780470293836
Nonparametrics for Sensory Science by J. C. W. Rayner,D. J. Best,Per Bruun Brockhoff,G. D. Rayner Pdf
Sensory evaluation is the perception science of the food industry. Sensory data can be costly to obtain and so gleaning the most information possible from the data is key. Increasingly, value is added to sensory evaluation by the use of statistics, especially to improve the quality of product development and to make the most of market research. Nonparametrics for Sensory Science is written to complement existing parametric methodology. Nonparametric methods are appropriate when facts are only available in nominal or ordinal form, and when the model assumptions necessary for parametric procedures do not hold. Author Rayner and his colleagues consider problems including the most commonly occurring and important experimental designs: the one-sample, k-sample, blocked samples, samples with factorial structure and samples with correlation structure. Innovative new techniques are outlined and complemented with real examples. Techniques described may be applied to data where the traditional, most frequently applied nonparametric tests, such as the Kruskal-Wallis, the Friedman and the Spearman tests, are applied. Those familiar with traditional nonparametric testing will be able to update their knowledge, acquiring powerful new methods. Those without prior knowledge of nonparametric testing will be able to acquire that knowledge through this book. Aimed at sensory scientists and statisticians interested in nonparametrics, the techniques of Nonparametrics for Sensory Science are of broad general interest, but are of particular interest in sensory evaluation applications.