Abstract

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

"...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