Resampling Methods A Practical Guide to Data Analysis

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, the book provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware.
Topics and Features
- Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work.
- Includes a systematic guide to selecting the correct procedure for a particular application.
- Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling.
- Suitable for both classroom use and individual self-study.
New to the Third Edition
- Procedures are grouped by application; a prefatory chapter guides readers to the appropriate reading matter.
- Program listings and screen shots now accompany each resampling procedure.
- To simplify programming, code for readers to download and apply is posted athttp://www.springeronline.com/0-8176-4386-9.
- Notation has been simplified and, where possible, eliminated.
- A glossary and answers to selected exercises are included.
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.
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Resampling Methods A Practical Guide to Data Analysis Fast Download
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