Mathematical Statistics with Resampling and R

Mathematical Statistics with Resampling and R

• Used Book in Good Condition

<b>This book bridges the latest software applications with the benefits of modern resampling techniques</b> <p>Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, M<i>athematical Statistics with Resampling and R</i> utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques.</p> <p>The book begins by introducing permutation tests and bootstrap methods, motivating classical inference methods. Striking a balance between theory, computing, and applications, the authors explore additional topics such as:</p> <ul> <li>Exploratory data analysis</li> <li>Calculation of sampling distributions</li> <li>The Central Limit Theorem</li> <li>Monte Carlo sampling</li> <li>Maximum likelihood estimation and properties of estimators</li> <li>Confidence intervals and hypothesis tests</li> <li>Regression</li> <li>Bayesian methods</li> </ul> <p>Throughout the book, case studies on diverse subjects such as flight delays, birth weights of babies, and telephone company repair times illustrate the relevance of the real-world applications of the discussed material. Key definitions and theorems of important probability distributions are collected at the end of the book, and a related website is also available, featuring additional material including data sets, R scripts, and helpful teaching hints.</p> <p><i>Mathematical Statistics with Resampling and R</i> is an excellent book for courses on mathematical statistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians working in the areas of business, economics, biostatistics, and public health who utilize resampling methods in their everyday work.</p>