This self-contained, comprehensive treatment of variance and regression analysis, is suitable for students and researchers who may not have a calculus background. Models, tests, assumptions and confidence intervals allow readers to locate the material, know when to do the analysis, and correctly interpret results. New information in this edition, not found in other texts at this level, includes discussions of widely used computer programs to perform the analysis, and a new chapter on repeated measures designs.
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A valuable new edition of a standard in the field of statistics
For the ever–increasing number of practitioners who must perform sophisticated statistical analyses on computers, Applied Statistics: Analysis of Variance and Regression has long been a standard reference and text. This new Third Edition has been thoroughly revised to provide a comprehensive and up–to–date combination of sound statistical methodology, practical advice on the application of this methodology, and interpretation of output from statistical programs.
Special features of this edition include:
Eminently suitable for students and researchers who may not have a calculus background as well as for more advanced practitioners, this self–contained, comprehensive treatment of variance and regression analysis readies a new generation of researchers for the demands of this growing field.
The Wiley Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
". . . overall this is an excellent book . . . I recommend this book to everyone . . ."
Statistical Methods in Medical Research
". . . it contains a wealth of useful up–to–date information and examples from the health sciences."
Technometrics
Applied Statistics: Analysis of Variance and Regression, Third Edition has been thoroughly revised to provide a comprehensive and up–to–date combination of sound statistical methodology, practical advice on the application of this methodology, and interpretation of output from statistical programs. Special features include comprehensive treatment of each topic, from summarization of data to presentation of results; a greater emphasis on regression, data screening, and confidence intervals; in–depth discussion of design–related topics such as mixed models and random effects; and overviews of more advanced topics. This valuable, self–contained textbook is eminently suitable for upper–undergraduate/graduate students and applied researchers with an interest in ANOVA techniques.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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