3rd ed. - Amsterdam ; Boston : Elsevier/Academic Press, 2012.
xxi, 690 p. : ill ; 25 cm.
Introduction to robust estimation & hypothesis testing
Includes bibliographical references (p. 631-685) and index.
Machine generated contents note: 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.
"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"-- Provided by publisher.