This groundbreaking book shows how apply modern resampling techniques to mathematical statistics. The book includes permutation tests and bootstrap methods and classical inference methods. Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The use of R throughout the book underscores the significance of resampling since its implementation is fast enough to be both convenient and explanatory. While computer clock speeds have leveled off, new multi-core computers are well suited for parallel applications like resampling. The book contains examples, figures, exercise sets, case studies, and helpful remarks. An author-maintained web site is available.