R for Statistics (Paperback)

Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples.

Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R.

Focusing on the R software, the first section covers:

• Basic elements of the R software and data processing
• Clear, concise visualization of results, using simple and complex graphs
• Programming basics: pre-defined and user-created functions

The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including:

• Regression methods
• Analyses of variance and covariance
• Classification methods
• Exploratory multivariate analysis
• Clustering methods
• Hypothesis tests

After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.

Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat

儘管現在有許多適合現代統計學家使用的軟體套件，但R具有全面、廣泛和免費的三重優勢。《Statistiques avec R》第二版於2008年出版，在法語世界成為R指南的經典之作。經過翻譯和更新，《R for Statistics》增加了許多擴展和額外的實例。

本書分為兩個部分，首先關注R軟體，然後介紹如何使用R實施傳統統計方法。

關於R軟體，第一部分包括：

- R軟體的基本元素和資料處理
- 使用簡單和複雜圖表清晰、簡潔地呈現結果
- 編程基礎：預定義和用戶創建的函數

本書的第二部分介紹了R方法應用於各種傳統統計資料處理技術，包括：

- 迴歸方法
- 方差和共變異數分析
- 分類方法
- 探索性多變量分析
- 聚類方法
- 假設檢驗

在簡要介紹方法後，本書詳細說明了R命令行並提供了註解的結果。《R for Statistics》對於初學者和專家都易於理解，是任何科學家的清晰且愉快的資源。

本書的網頁（http://www.agrocampus-ouest.fr/math/RforStat）提供了本書中描述的資料集和所有結果。