Resampling Methods: A Practical Guide to Data Analysis

The goal of this book is to introduce statistical methodology-estimation, hypothesis, testing and classification-to a wide applied audience through resampling from existing data via the bootstrap, and estimation or cross-validation methods. The book provides an accessible introduction and practical guide to the power, simplicity and veritability of the bootstrap, cross-validation and permutation tests. Industrial statistical consultants, professionals and researchers will find the book's methods and software imimediately helpful. (unvollstandig)) This Second edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. It is an essential resource for industrial statisticians, statistical consultants, and research professionals in science, engineering, and technology. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercizes, practical data sets, and freely available statistical shareware. Topics and features: *Thoroughly revised text features more practical examples plus an additional chapter devoted to regression and data mining techniques and their limitations *Uses resampling approach to introduction statistics *A Practical presentation that covers all three sampling methods - bootstrap, density-estimation, and permutations *Includes systematic guide to help one select correct procedure for a particular application *Detailed coverage of all three statistical methodologies - classification, estimation, and hypothesis testing *Suitable for classroom use and individual, self-study purposes *Numerous practical examples using popular computer programs such as SAS, Stata, and StatXact *Useful appendices with computer programs and code to develop own methods *Downloadable freeware from author's website: http://users.oco.net/drphilgood/resamp.htm With its accessable style and intuitive topic development, the book is an excellent basic resource and guide to the power, simplicity and versatility of bootstrap, cross-validation and permutation tests. Students, professionals, and researchers will find it a particularly useful guide to modern resampling methods and their applications.