Title
Resampling Methods: A Practical Guide To Data Analysis,Used
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This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, crossvalidation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a tablefree 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 addin), EViews, MATLAB, R, Resampling Stats, SAS macros, SPlus, 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.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What topics are covered in 'Resampling Methods: A Practical Guide to Data Analysis'? A: This book covers a variety of topics including the bootstrap, cross-validation, permutation tests, classification, estimation, experimental design, hypothesis testing, and modeling.
- Q: Is this book suitable for beginners in data analysis? A: Yes, the book is designed to be accessible, requiring only minimal mathematics beyond algebra, making it suitable for beginners and those new to data analysis.
- Q: What is new in the third edition of this book? A: The third edition includes grouped procedures by application, program listings with screenshots for resampling procedures, simplified notation, and a glossary with answers to selected exercises.
- Q: Can I find code examples online for this book? A: Yes, code for various resampling methods discussed in the book can be downloaded from http://www.springeronline.com/0-8176-4386-9.
- Q: How many pages does the book have? A: The book contains 238 pages.
- Q: What is the binding type of the book? A: The book is available in hardcover binding.
- Q: Who is the author of this book? A: The book is authored by Phillip I. Good.
- Q: What is the publication date of this book? A: The book was published on September 8, 2005.
- Q: Is this book appropriate for self-study? A: Yes, it is suitable for both classroom use and individual self-study, featuring numerous exercises and practical datasets.
- Q: What audience is this book aimed at? A: The book is intended for statisticians, biostatisticians, statistical consultants, students, and research professionals across various fields including biological, physical, and social sciences.