Phillip I. Good Libri

This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.

The book provides a comprehensive theoretical foundation in hypothesis testing and decision theory, tailored for practitioners and trainers in statistics and biostatistics. It emphasizes the shift towards distribution-free permutation methods as the primary approach for hypothesis testing, driven by the need for powerful statistical tools, regulatory demands for exact significance levels, and the complexities of real-world data. While it advocates for permutation tests, it also acknowledges the continued relevance of certain robust parametric tests like Student's t in statistical practice.

"This book provides a step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering. Its intuitive and informal style ideally makes it suitable as a text for students and researchers, whether experienced or coming to these resampling methods for the very first time. The real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length."--BOOK JACKET.