Resampling Methods : A Practical Guide to Data Analysis
Language: English
Published by Birkhäuser, 2005
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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£ 94.05
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Druck auf Anfrage Neuware - Printed after ordering.
Seller Inventory # 9780817643867
- Title
- Resampling Methods : A Practical Guide to Data Analysis
- Author
- Phillip I. Good
- Publisher
- Birkhäuser
- Publication year
- 2005
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0817643869
- ISBN 13
- 9780817643867
- Edition
- 3rd Edition
- Item weight
- 532 grams
- Dimensions
- 241x160x19 mm
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
"…the author has packaged an excellent and modern set of topics around the development and use of quantitative models.... If you need to learn about resampling, this book would be a good place to start."
―Technometrics (Review of the Second Edition)
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: Whether one programs in C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-PLUS, Stata, or StatXact, readers will find the program listings and screen shots needed to put each resampling procedure into practice.
* To simplify programming, code for readers to download and apply is posted at http://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.
"About the title" may belong to another edition of this title.
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