A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling - Phillip Good

Resampling methods-techniques for repeatedly resampling data to obtain results-are being used in virtually every research area. This practical guide discusses the applications of these methods in a wide variety of subject areas. Each chapter contains a wealth of examples along with R and Stata code for implementing the techniques. Written by a leading authority in the field, the text covers estimation, two-sample and k-sample univariate, and multivariate comparisons of means and variances, sample size determination, categorical data analysis, multiple hypotheses, and model building.