R for Statistics (Paperback)
暫譯: R 與統計學 (平裝本)

Pierre-Andre Cornillon

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商品描述

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

商品描述(中文翻譯)

雖然目前有各種適合現代統計學家的軟體包,但 R 擁有全面性、普及性和免費的三重優勢。2008 年出版的《Statistiques avec R》第二版在法語世界中作為 R 的指南書籍取得了巨大的成功。經過翻譯和更新的《R for Statistics》包含了許多擴展和額外的實作範例。

本書分為兩個部分,首先聚焦於 R 軟體,然後探討如何使用 R 實現傳統統計方法。

第一部分專注於 R 軟體,涵蓋以下內容:
- R 軟體的基本元素和數據處理
- 使用簡單和複雜圖形清晰、簡潔地可視化結果
- 程式設計基礎:預定義和用戶創建的函數

本書的第二部分介紹了 R 方法,涵蓋各種傳統統計數據處理技術,包括:
- 迴歸方法
- 方差和協方差分析
- 分類方法
- 探索性多變量分析
- 聚類方法
- 假設檢定

在簡短介紹方法後,本書詳細說明了 R 命令行並提供註解結果。《R for Statistics》對於新手和專家都很友好,是任何科學家的清晰且愉快的資源。

資料集和本書中描述的所有結果可在本書的網頁上獲得,網址為 http://www.agrocampus-ouest.fr/math/RforStat