Permutation, Parametric, and Bootstrap Tests of Hypotheses

Phillip I. Good - Collection Springer Series In Statistics

315 pages, parution le 11/02/2005 (3^eme édition)

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Résumé

This text will equip both practitioners and theorists with the necessary background in testing hypothesis and decision theory to enable innumerable practical applications of statistics. Its intuitive and informal style makes it suitable as a text for both students and researchers. It can serve as the basis for a one- or two-semester graduate course as well as a standard handbook of statistical procedures for the practitioners' desk.

Parametric, permutation, and bootstrap procedures for testing hypotheses are developed side by side. The emphasis on distribution-free permutation procedures will enable workers in applied fields to use the most powerful statistic for their applications and satisfy regulatory agency demands for methods that yield exact significance levels, not approximations. Algebra and an understanding of discrete probability will take the reader through all but the appendix, which utilizes probability measures in its proofs.

The revised and expanded text of the Third Edition (previously called Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses) includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. Real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length. New sections are added on sequential analysis and multi-variate analysis plus a chapter on the exact analysis of multi-factor designs based on the recently developed theory of synchronous permutations.

The book's main features include:

Detailed consideration of one-, two-, and fc-sample tests, contingency tables, clinical trials, cluster analysis, multiple comparisons, multivariate analysis, and repeated measures
Numerous practical applications in archeology, biology, business, climatology, clinical trials, economics, education, engineering, geology, law, medicine, and the social sciences
Valuable techniques for reducing computation time
Practical advice on experimental design
Sections on sequential analysis
Comparisons among competing bootstrap, parametric, and permutation techniques

From a review of the First Edition:

"Permutation Tests is a welcome addition to the literature on this subject and will prove a valuable guide for practitioners ... This book has already become an important addition to my reference library. Those interested in permutation tests and its applications will enjoy reading it."
(Journal of the American Statistical Association)

From a review of the Second Edition:

"Permutation Tests is superb as a resource for practitioners. The text covers a broad range of topics, and has myriad pointers to topics not directly addressed ... the book gives guidance and inspiration to encourage developing one's own perfectly tailored statistics ... The writing is fun to read."
(John I. Marden)

L'auteur - Phillip I. Good

PHILLIP I. GOOD, PhD, is an Operations Manager for Information Research in Huntington Beach, California. He is the author of A Manager's Guide to the Design and Conduct of Clinical Trials, published by Wiley, as well as numerous other books.

Sommaire

A Wide Range of Applications
Optimal Procedures
Testing Hypotheses
Distributions
Multiple Tests
Experimental Designs
Multifactor Designs
Categorical Data
Multivariate Analysis
Clustering in Time and Space
Coping with Disaster
Solving the Unsolved and the Insolvable
Publishing Your Results
Increasing Computational Efficiency
Appendix: Theory of Testing Hypotheses

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Phillip I. Good
Collection	Springer Series In Statistics
Parution	11/02/2005
Édition	3^eme édition
Nb. de pages	315
Format	16 x 24
Couverture	Relié
Poids	610g
Intérieur	Noir et Blanc
EAN13	9780387202792
ISBN13	978-0-387-20279-2