1. One-sample problems -- 2. Two-sample problems -- 3. Linear models -- 4. Experimental designs : fixed effects -- 5. Models with dependent error structure -- 6. Multivariate.

Summary: "Often referred to as distribution-free methods, nonparametric methods do not rely on assumptions that the data are drawn from a given probability distribution. With an emphasis on Wilcoxon rank methods that enable a unified approach to data analysis, this book presents a unique overview of robust nonparametric statistical methods. Drawing on examples from various disciplines, the relevant R code for these examples, as well as numerous exercises for self-study, the text covers location models, regression models, designed experiments, and multivariate methods. This edition features a new chapter on cluster correlated data"-- Provided by publisher.

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"Often referred to as distribution-free methods, nonparametric methods do not rely on assumptions that the data are drawn from a given probability distribution. With an emphasis on Wilcoxon rank methods that enable a unified approach to data analysis, this book presents a unique overview of robust nonparametric statistical methods. Drawing on examples from various disciplines, the relevant R code for these examples, as well as numerous exercises for self-study, the text covers location models, regression models, designed experiments, and multivariate methods. This edition features a new chapter on cluster correlated data"-- Provided by publisher.

Includes bibliographical references (p. 495-520) and indexes.

1. One-sample problems -- 2. Two-sample problems -- 3. Linear models -- 4. Experimental designs : fixed effects -- 5. Models with dependent error structure -- 6. Multivariate.