Abstract
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 Monographs on statistics and applied probability (Series), 113
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CITATION STYLE
Stoimenova, E. (2012). Robust nonparametric statistical methods. Journal of Applied Statistics, 39(6), 1383–1384. https://doi.org/10.1080/02664763.2012.657414
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