R for Statistics - Cornillon, Pierre-Andre

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Résumé :
This text explores the use of R for classical statistical analysis. The first half of the book introduces R, data manipulation and visualization, statistical models, graphics, and R programming. The second half presents various statistical analysis techniques by first introducing the data example, then describing the problem to solve, and finally conducting the analysis using R. This example-based approach enables readers to replicate the analyses using their own data. Some of the techniques covered include simple regression, multiple regression, ANOVA, logistic regression, principal component analysis, and clustering....

Sommaire:
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Section 4.2 on the apply family of functions and related functions for matrices, arrays, and data frames is by far the most friendly and helpful introduction to the subject that I have seen. ... All datasets, along with the R-code in the book, are available on the website for the text. ... If you are not a trained programmer but you aspire to write code that is efficient and perhaps, from time to time, clever, then this book is a fine place for you to start learning R. -Homer S. White, MAA Reviews, January 2013 [T]he book is accessible for statisticians of all levels and areas of expertise as well as for novice and advanced R users. ... I recommend it for anyone who wants to learn about the why and how of the most commonly employed statistical methods and their extensions. -Irina Kukuyeva, Journal of Statistical Software, Vol. 51, November 2012