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Introduction to Robust Estimation and Hypothesis Testing,

Edition 5

Editors: By Rand R. Wilcox

Publication Date: 24 Nov 2021

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Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful ‘how-to’ on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity that can provide substantial gains in power. Coverage includes techniques for comparing groups and measuring effect size, current methods for comparing quantiles, and expanded regression methods for both parametric and nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are included to support comprehension and practice.

Key Features

Includes the latest developments in robust regression
Provides many new, improved and accessible R functions
Offers comprehensive coverage of ANOVA and ANCOVA methods

About the author

By Rand R. Wilcox, University of Southern California, USA

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
12. ANCOVA