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Nonparametric Statistical Inference


Nonparametric Statistical Inference
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Nonparametric Statistical Inference


Nonparametric Statistical Inference
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2020-12-21

Nonparametric Statistical Inference written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-21 with Mathematics categories.


Praise for previous editions: "... a classic with a long history." – Statistical Papers "The fact that the first edition of this book was published in 1971 ... [is] testimony to the book’s success over a long period." – ISI Short Book Reviews "... one of the best books available for a theory course on nonparametric statistics. ... very well written and organized ... recommended for teachers and graduate students." – Biometrics "... There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics "... Useful to students and research workers ... a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics. The Sixth Edition carries on this tradition and incorporates computer solutions based on R. Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new references Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.



Nonparametric Statistical Inference


Nonparametric Statistical Inference
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2014-03-10

Nonparametric Statistical Inference written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-10 with Mathematics categories.


Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.



Nonparametric Statistical Inference


Nonparametric Statistical Inference
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2020-12-22

Nonparametric Statistical Inference written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-22 with Mathematics categories.


Praise for previous editions: "... a classic with a long history." – Statistical Papers "The fact that the first edition of this book was published in 1971 ... [is] testimony to the book’s success over a long period." – ISI Short Book Reviews "... one of the best books available for a theory course on nonparametric statistics. ... very well written and organized ... recommended for teachers and graduate students." – Biometrics "... There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics "... Useful to students and research workers ... a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics. The Sixth Edition carries on this tradition and incorporates computer solutions based on R. Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new references Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.



Lecture Notes On Nonparametric Statistical Inference


Lecture Notes On Nonparametric Statistical Inference
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Author : Edwin James George Pitman
language : en
Publisher:
Release Date : 1948

Lecture Notes On Nonparametric Statistical Inference written by Edwin James George Pitman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1948 with categories.




Nonparametric Statistical Inference Fourth Edition


Nonparametric Statistical Inference Fourth Edition
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2003-05-09

Nonparametric Statistical Inference Fourth Edition written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-09 with Mathematics categories.


Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.



Nonparametric Techniques In Statistical Inference


Nonparametric Techniques In Statistical Inference
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Author : Madan Lal Puri
language : en
Publisher:
Release Date : 1970-11-02

Nonparametric Techniques In Statistical Inference written by Madan Lal Puri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970-11-02 with Mathematics categories.


This book, the proceedings of the first international symposium, surveys the current status of nonparametric theory. It contains thirty-five papers with discussions by some of the world's most eminent authorities in the field. The subjects discussed are testing and estimation, order statistics and allied problems, ranking and selection procedures, general theory, problems, relating to goodness - of -fit, decision theoretic and empirical Bayes procedures, and nonparametric methods and elementary statistics. (Author).



Nonparametric Statistical Inference Fifth Edition


Nonparametric Statistical Inference Fifth Edition
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Author : Jean Dickinson Gibbons
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2010-07-26

Nonparametric Statistical Inference Fifth Edition written by Jean Dickinson Gibbons and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-26 with Mathematics categories.


Proven Material for a Course on the Introduction to the Theory and/or on the Applications of Classical Nonparametric Methods Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametric statistics. The fifth edition carries on this tradition while thoroughly revising at least 50 percent of the material. New to the Fifth Edition Updated and revised contents based on recent journal articles in the literature A new section in the chapter on goodness-of-fit tests A new chapter that offers practical guidance on how to choose among the various nonparametric procedures covered Additional problems and examples Improved computer figures This classic, best-selling statistics book continues to cover the most commonly used nonparametric procedures. The authors carefully state the assumptions, develop the theory behind the procedures, and illustrate the techniques using realistic research examples from the social, behavioral, and life sciences. For most procedures, they present the tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of other relevant procedures. The text also gives examples of computer applications based on Minitab, SAS, and StatXact and compares these examples with corresponding hand calculations. The appendix includes a collection of tables required for solving the data-oriented problems. Nonparametric Statistical Inference, Fifth Edition provides in-depth yet accessible coverage of the theory and methods of nonparametric statistical inference procedures. It takes a practical approach that draws on scores of examples and problems and minimizes the theorem-proof format. Jean Dickinson Gibbons was recently interviewed regarding her generous pledge to Virginia Tech.



Nonparametric Inference


Nonparametric Inference
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Author : Z. Govindarajulu
language : en
Publisher: World Scientific
Release Date : 2007

Nonparametric Inference written by Z. Govindarajulu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.


This book provides a solid foundation on nonparametric inference for students taking a graduate course in nonparametric statistics and serves as an easily accessible source for researchers in the area. With the exception of some sections requiring familiarity with measure theory, readers with an advanced calculus background will be comfortable with the material.



Nonparametric Statistical Methods


Nonparametric Statistical Methods
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Author : Myles Hollander
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-25

Nonparametric Statistical Methods written by Myles Hollander and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-25 with Mathematics categories.


Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.



Applied Nonparametric Statistical Methods


Applied Nonparametric Statistical Methods
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Author : Nigel Smeeton
language : en
Publisher: CRC Press
Release Date : 2025-03-31

Applied Nonparametric Statistical Methods written by Nigel Smeeton and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Mathematics categories.


Nonparametric statistical methods minimize the number of assumptions that need to be made about the distribution of data being analysed, unlike classical parametric methods. As such, they are an essential part of a statistician’s armoury, and this book is an essential resource in their application. Starting from the basics of statistics, it takes the reader through the main nonparametric approaches with an emphasis on carefully explained examples backed up by use of the R programming language. Key features of this fully revised and extended fifth edition include the following: An introductory chapter that provides a gentle introduction to the basics of statistics, including types of data, hypothesis testing, confidence intervals and ethical issues An R package containing functions that have been written for the examples in the text and the exercises Summary bullet points at the end of each section to enable the reader to locate important principles quickly A case study from medical research to demonstrate nonparametric approaches to the data analysis Examples fully integrated into the text, drawn from published research on contemporary issues, with more detail given in their explanation Extensive exercises along with complete solutions that allow the reader to test their understanding of the material Articles used in the examples and exercises carefully chosen to enable readers to identify up-to-date literature in their field for research, publications and teaching material Numerous historical references throughout the text, from which to explore the origins of nonparametric methods Applied Nonparametric Statistical Methods, Fifth Edition, is a comprehensive course text in nonparametric techniques suitable for undergraduate students of mathematics and statistics. It assumes only basic previous experience of statistics, and with algebra kept to a minimum, it is also ideal for quantitative methods modules delivered to undergraduate or postgraduate students in science, business and health service training. It is an invaluable resource for researchers, medical practitioners, business managers, research and development staff, and others needing to interpret quantitative information. Suitable for self-directed learning in continuing professional development, it also acts as a handy accessible reference manual.