What sets this book apart from other mathematical statistics books is the use of modern resampling techniques. The authors begin with permutation tests and bootstrap methods before introducing 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 of resampling since its implementation is fast enough to be both convenient and explanatory. Furthermore, while computer clock speeds have leveled off, new multi-core computers are well suited for parallel applications like resampling. The book is full of examples, figures, exercise sets, case studies, and helpful remarks. An author-maintained web site is available; it includes additional content, more data sets, and programming scripts for computer-savvy readers.