Mathematical Statistics with Resampling and R (Hardcover)
Laura M. Chihara, Tim C. Hesterberg
- 出版商: Wiley
- 出版日期: 2011-09-06
- 售價: $5,140
- 貴賓價: 9.5 折 $4,883
- 語言: 英文
- 頁數: 432
- 裝訂: Hardcover
- ISBN: 1118029852
- ISBN-13: 9781118029855
-
相關分類:
R 語言、機率統計學 Probability-and-statistics
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商品描述
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.