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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: How many pages does this book have? A: This book has two hundred thirty-eight pages. It provides comprehensive coverage of resampling methods and their applications in data analysis.
- Q: What are the dimensions of this book? A: The book measures six point thirty-eight inches in length, zero point sixty-three inches in width, and nine point thirty-eight inches in height. These dimensions make it a convenient size for both reading and referencing.
- Q: What binding type does this book have? A: This book is hardcover bound. The hardcover ensures durability and a professional appearance suitable for both personal and academic use.
- Q: Is this book suitable for beginners? A: Yes, this book is suitable for beginners. It requires minimal mathematics beyond algebra and offers a clear introduction to resampling methods for data analysis.
- Q: Can I use this book for self-study? A: Yes, this book is ideal for self-study. It includes numerous exercises and practical datasets that facilitate individual learning.
- Q: What topics are covered in this book? A: The book covers topics such as bootstrap methods, cross-validation, and permutation tests. It also includes classification, estimation, and hypothesis testing.
- Q: How do I keep the book in good condition? A: To keep the book in good condition, store it in a cool, dry place and avoid exposing it to direct sunlight. Handle it carefully to prevent damage to the cover and pages.
- Q: Are there any online resources available with this book? A: Yes, there are online resources available. Program code and details for application can be downloaded from the publisher's website.
- Q: Is this book appropriate for advanced students? A: Yes, this book is also appropriate for advanced students. It offers detailed coverage and systematic guidance suitable for various academic levels.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact the seller for return or exchange options. Most retailers have customer support to assist with such issues.
- Q: Does this book include a glossary? A: Yes, this book includes a glossary. The glossary provides definitions of key terms used throughout the text, enhancing understanding.
- Q: Are exercises included in this book? A: Yes, the book includes numerous exercises. These exercises are designed to reinforce learning and apply the concepts discussed in the chapters.
- Q: Is this book recommended for professionals? A: Yes, this book is recommended for professionals. It serves as an essential resource for statisticians, biostatisticians, and research professionals in various fields.
- Q: Can I use this book for classroom instruction? A: Yes, this book can be used for classroom instruction. Its structured approach and practical examples make it suitable for teaching and learning.
- Q: What is the author's name? A: The author of this book is Phillip I. Good. He is known for his expertise in statistical methods and data analysis.