Mathematical Statistics with Resampling and R 2nd Edition

<p><b>This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques</b> <p>Resampling helps students understand the meaning of sampling distributions, sampling variability, <i>P</i>-values, hypothesis tests, and confidence intervals. The second edition of <i>Mathematical Statistics with Resampling and R</i> combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. <p>This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications. <p>Throughout the book, new and updated case studies representing a diverse range of subjects such as flight delays, birth weights of babies, and U.S demographics and views on sociological issues illustrate the relevance of mathematical statistics to real-world applications. <p>Changes and additions to the second edition include: <ul> <li>New material on topics such as paired data, Fisher’s Exact Test and the EM algorithm</li> <li>A new chapter on ANOVA</li> <li>A “Google Interview Question” case study and discussion that illustrate statistical thinking—starting with understanding the problem and framing it properly before proceeding to solutions</li> <li>New exercises and examples, updated case studies, data sets, and R code</li> </ul> <p>Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of <i>Mathematical Statistics with Resampling and R</i> presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.