An Introduction to R
by W. N. Venables, D. M. Smith
Publisher: Network Theory 2008
Number of pages: 100
This manual provides a comprehensive introduction to R, a software package for statistical computing and graphics. R supports a wide range of statistical techniques, and is easily extensible via user-defined functions written in its own language, or using dynamically loaded modules written in C, C++ or Fortran. One of R's strengths is the ease with which well-designed publication-quality plots can be produced.
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by Sivakumaran Raman - Smashwords
Learn R programming for data analysis in a single day. The book aims to teach data analysis using R within a day to anyone who already knows some programming in any other language. The book has sample code which can be downloaded as a zip file.
by Vincent Zoonekynd
Contents: Introduction to R; Programming in R; From Data to Graphics; Customizing graphics; Factorial methods; Clustering; Probability Distributions; Estimators and Statistical Tests; Regression; Other regressions; Regression Problems; etc.
by Patrick Burns - Burns Statistics
If you don't know of 'The R Inferno', this revised edition is a book-length (intermediate level) explanation of a few trouble spots when using the R language. If you are using R and you think you're in hell, this is a map for you.
by Julian J. Faraway
The emphasis of this text is on the practice of regression and analysis of variance. The objective is to learn what methods are available and when they should be applied. Many examples are presented to clarify the use of the techniques.