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. Key Features * Covers latest developments in robust regression * Covers latest improvements in ANOVA * Includes newest rank-based methods * Describes and illustrated easy to use software 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