Nonparametric Statistical Inference

This book PDF is perfect for those who love Mathematics genre, written by Jean Dickinson Gibbons and published by CRC Press which was released on 21 December 2020 with total hardcover pages 695. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Nonparametric Statistical Inference books below.

Nonparametric Statistical Inference
Author : Jean Dickinson Gibbons
File Size : 43,7 Mb
Publisher : CRC Press
Language : English
Release Date : 21 December 2020
ISBN : 9781351616171
Pages : 695 pages
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Nonparametric Statistical Inference by Jean Dickinson Gibbons Book PDF Summary

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

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

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Nonparametric Statistical Inference

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

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Nonparametric Statistical Inference  Fourth Edition

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

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Nonparametric Statistical Inference

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

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Nonparametric Statistical Inference  Fifth Edition

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

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Applied Nonparametric Statistical Methods  Fourth Edition

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

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Handbook of Parametric and Nonparametric Statistical Procedures

With more than 500 pages of new material, the Handbook of Parametric and Nonparametric Statistical Procedures, Fourth Edition carries on the esteemed tradition of the previous editions, providing up-to-date, in-depth coverage of now more than 160 statistical procedures. The book also discusses both theoretical and practical statistical topics, such as experimental design,

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Nonparametric Inference

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

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