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Mathematical Statistics with Resampling and R
Publisher: John Wiley & Sons
Pub. Date: September 6, 2011
Print ISBN: 978-1-118-02985-5
Web ISBN: 1-118029-85-2
Pages in Print Edition: 432
Subscriber Rating:
[2 Ratings] Subscriber Reviews
Overview
This book bridges the latest software applications with the benefits of modern resampling techniques
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, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques.
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:
Exploratory data analysis
Calculation of sampling distributions
The Central Limit Theorem
Monte Carlo sampling
Maximum likelihood estimation and properties of estimators
Confidence intervals and hypothesis tests
Regression
Bayesian methods
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.
Mathematical Statistics with Resampling and R 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.
Subscriber Reviews
Average Rating: 
Based on 2 Ratings
"The middle road, but Calculus required" - by Dzhaughn on 23-JAN-2012
Reviewer Rating: 
Not an introduction to prob and stats, nor a how-to, nor an introduction to R. But assuming basic calculus and a course in probability (the appendix helps if you are merely rusty) introduces the main themes of statistics with a wholesome definition/theorem/corollary exposition. The strength of this book is how it organizes the mathematical exposition around simple questions about concrete data sets. The data sets are first explored with simulation (using R, patiently presented), and the definitions and theorems flow from there.
The book endeavors to convey how Statistics is an expression (and a rather groping expression) in mathematical language of phenomena that arise from sampling data from unknown populations. An ambitious goal, fairly accomplished.
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"One of the best books on Mathematical Statistics" - by Shamal Jayakody on 26-NOV-2011
Reviewer Rating:
This is a very good book on Mathematical Statistics. It is very practical and useful.
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Top Level Categories:
Information Technology & Software Development
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Information Technology & Software Development > Programming
Programming > R
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