Jean Dickinson Gibbons – författare

This SIAM Classics edition is an unabridged, corrected republication of the work first published in 1977. It provides a compendium of applied aspects of ordering and selection procedures and includes tables that permit the practitioner to carry out the experiment and draw statistically justified conclusions. These tables are not readily available in other texts. Although more than 1000 papers and several books on the general theory of ranking and selection have been published since this book first appeared, the methodology is presented in a more elementary fashion, with numerous examples to help the reader apply it to a specific problem.There is a dichotomy in modern statistics that distinguishes between analyses done before an experiment is completed and those done afterward. Ranking and selection methods are useful in both of these categories. The authors provide an alternative to the overused ""testing the null hypothesis"" when what the practitioner really needs is a method of ranking k given populations, selecting the t best populations, or some similar goal. That need and purpose is as important today as when the subject was first developed nearly 50 years ago.

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 AssociationSince 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 referencesNonparametric 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.

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.