R (Tutorials and Readings)

Introduction to R

R is an open source (FREE) program for statistical computing and graphics. It was developed from the S language by John Chambers and colleagues and is very similar to a commercial statistics package called S-Plus. Because R is free and available for all major platforms (mac, pc, linux), learning R means learning a main-stream software package that you can install at home or at work.

R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Here are only two examples of the amazing graphical abilities R has:

(Graphs provided by: http//addictedtor.free.fr/graphiques)

eyboard or typed in a text file and accessed. The advantage of this is that it is very flexible to add different options to a command. The disadvantage is that it takes a little time to learn the commands. Luckily, many of the commands in R are intuitive and there is a graphical user interface (GUI) called R-commander that can be installed from within R (it's installed by default in the CAL).

To get general information about what R has to offer you go to their website: http://www.r-project.org/

R Installation Guides

R Installation Guide - Windows
R Installation Guide - MAC - requires X11 module

List of Scientific Computing's recommended R packages with descriptions.

Ubuntu Linux (currently the only Linux version supported by Scientific Computing) includes a direct access command for the installation of R:

sudo apt-get update




   sudo apt-get install r-base

R Readings and Tutorials

R Reference Card
A reference of commands and code.

R for Beginners by Emmanuel Paradis
A lengthy introduction to R, that covers data, graphics, statistical analysis and programming in R.

Practical Regression and ANOVA by Julian J. Faraway
An advanced book on Regression and analysis of variance that assumes knowledge of data analysis, calculus and linear algebra.

Ecology and Epidemiology in R (online) by K. A. Garrett, P. D. Esker, and A. H. Sparks
Applications of R in biology and basic programming.

Graphics in R by Paul Murrell
A guide to doing beginning and advanced graphics in R.

Introduction to Statistical Computing in R by John Fox
A guide to doing statistical computing in R.

Introductory Statistics in R by W. N. Venables, D. M. Smith and the R Development Core Team
A well-written guide to using R to do basic statistics.

R Introduction in PDF form by John Verzani
A PDF of a power point of an introduction to R. Detailed and well-written.

The R Foundation
The official website for R; click on "Mailing Lists" on the left hand side to sign up for the list-serves for R. The R "help" list-serve is high traffic, but necessary if R is going to be your statistical package of choice.

Time Series in R By Simon Jackman
Code for doing time series and cross-sectional analysis in R.

Tips for R
A detailed list of tips for using R, including shortcuts.

Tutorial for R
An introductory tutorial to R, including step-by-step functions

UCLA's Academic Computing R Assistance
Extensive assistance for R from UCLA's Academic Computing Services. Includes links to power points, movies, and MP3s about using R.

Wikipedia: R
A user-written guide to working in R

Statistical Analysis: an Introduction using R
This online "book aims to introduce the principles of statistics and modern statistical analysis for a non-mathematical audience, using the free statistical package 'R'".

Quick-R by Robert I. Kabacoff, Ph.D.
"I created this website for experienced users of popular statistical packages such as SAS, SPSS, Stata, and Systat (although current R users should also find it useful). My goal is to help you quickly access this language in your work."