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More About This Textbook
Overview
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations.
Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables.
• Covers latest developments in robust regression
• Covers latest improvements in ANOVA
• Includes newest rank-based methods
• Describes and illustrated easy to use software
Audience: Researchers and students interested in regression or comparing groups using the improved techniques developed in recent years, i.e. applied statisticians who already have some training in statistics; researchers and students insocial science, economics, and business.
Editorial Reviews
From the Publisher
"...greatly enhanced...almost twice as large as the first edition. This would now seem to be a good book for everyone to have in their library."-TECHNOMETRICS, VOL. 47, 2005
"...an outstanding introduction to robust statistics, outlier detection and the bootstrap. There is, to my knowledge, no comparable book written at this level of accessibility." David Leblang, University of Colorado at Boulder.
"It is rather unique, this book. The message that the author aims to deliver is an important one. Most other textbooks aim to illustrate the standard story, using innovative illustrations or clearer exposition. So there is a lot of redundancy out there in statistics books. This book stands out as providing something new and clearly important." Sheila Kennison, Oklahoma State University
Booknews
Focuses on the practical aspects of modern, robust statistical methods for regression and analyzing variance, which have become extremely accurate and powerful compared to conventional approaches because of a combination of theoretical developments, improved and more flexible statistical methods, and computer power. Discusses the rationale and foundation of robust methods, comparing two groups, one-way and higher designs, correlation and related issues, a range of regression methods, and other aspects. Assumes the reader to have completed an introductory statistics course covering the analysis of variance. Annotation c. by Book News, Inc., Portland, Or.Product Details
Related Subjects
Meet the Author
Rand R. Wilcox has a Ph.D. in psychometrics, is a professor of psychology at the University of Southern California, and a Fellow of the Royal Statistics Society and American Psychological Society. He is an internationally recognized expert in the field of Applied Statistics and has concentrated much of his research in the area of ANOVA and Regression. He has authored twobooks and more than 130 journal articles.
Table of Contents
Preface
1. Introduction
2. A Foundation for Robust Methods
3. Estimating Measures of Location and Scale
4. Confidence Intervals in the One-Sample Case
5. Comparing Two Groups
6. Some Multivariate Methods
7. One-Way and Higher Designs for Independent Groups 8. Comparing Multiple Dependent Groups
9. Correlation and Tests of Independence
10. Robust Regression
11. More Regression Methods