Resampling Methods: A Practical Guide to Data Analysis

By Phillip I. Good

Book Overview

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 limitation

• Format: Hardcover
• Language: English
• ISBN: 0817642439
• ISBN13: 9780817642433
• Release Date: November 2001
• Publisher: Springer
• Length: 238 Pages
• Weight: 1.10 lbs.
• Dimensions: 0.7" x 6.3" x 9.4"