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.

Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling Numerous exercises, practical data sets, and freely available statistical shareware Suitable for classroom use and individual self-study Includes supplementary material: sn.pub/extras

Autorentext
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.

Inhalt
Software for Resampling.- Estimating Population Parameters.- Comparing Two Populations.- Choosing the Best Procedure.- Experimental Design and Analysis.- Categorical Data.- Multiple Variables and Multiple Hypotheses.- Model Building.- Decision Trees.