What is R?

R is an extraordinarily extensive programming environment for statistical computing, data analysis, and statistical/scientific graphics. It is open source and under continual improvement with add-on packages available from many professional statisticians around the world.

R is rapidly becoming the professional statistician's first choice among statistical software packages and this trend is also present among many researchers.

R is available for multiple OS's: Linux, MAC OS and Windows are all supported.

How to get started with R: Installation and Configuration

B. Dudek has prepared a short ppt on R installation for his statistics classes and it can be helpful:
Installing R Powerpoint

Installation instructions are adequate with resources available at the official R web sites:
R home page
Cran Mirror for installation of R (I usually use the Univ. Toronto mirror "probability")
Frequently Asked Questions about R Installation and Usage

Several other sites can provide installation instructions:
An R primer for Introductory Statistics (Larget, U Wisc)
R Installation and Administration from the official R site
Installation of R, R packages, and R environments (John Maindonald)
Video on R Installation from Texas A&M University

A nice trio of sites that can be used for entry points into R
(Recommendations based on Dan Mirman's website)

Have you written software code linger than ten lines?
If yes, then move to next question.
If no, then use Try R, from the O'reilly code school.

Do you need to (re)learn basic statistics?
If yes, then use Learning Statistics with R by Naniel Navarro, a very comprehensive site.
If no, then go to the next question:

Do you want more practice than the above links provide or did you answer no/yes to the above two questions, then:
Look at R Bootcamp by Jared Knowles

Introductory Documents on R usage

R Manuals from the Core Development Team (I find these core manuals to be more difficult than much other freely available documentation)
Quick R. Very nice set of pages that offer core instruction for novices and SPSS users
Simple R. Using R for Introductory Statistics (John Verzani)
Using R. John Maindonald
R for SPSS, SAS and STATA users. Bob Muenchen's resources.

Statistics with R. Vincent Zoonekynd's extensive compilation of R applications
UCLA Resources on R
A short course on R. Thomas Lumley
R Commander. John Fox

Russ Ihaka's Class Pages Some of the best instruction in R that I have seen can be found in Russ Ihaka's lecture notes that he has generously posted.

Videos on R Installation and Usage

Rvideos from Texas A&M University
R Statistics Playlist from You Tube
Jeromy Anglin's very nice compilation of R videos. Novice, intermediate and advanced instruction.
R Tutorial Videos from Decision Science

Text Editors and Integrated Programming Environments

Text Editors to use in conjunction with R:
Notepad ++ (strongly recommended)
Notepad2
VIM
EMACS

Integrated Programming Environments for use with R:
RStudio (THE DeFACTO standard for R users/programmers)

StatET and Eclipse. Also permits integration with Sweave (latex capability from R)

Learning about and keeping up with R functions and Packages

R Function Finder (Vanderbilt)
Task Views on R packages. Cran organization of packages by type of analysis
Cran listing of R packages, sorted by publication date
Cran listing of R packages, sorted by name
Crantastic (revisions to R packages)
Cranberries (new R packages)

Help, Blogs, Search Engines

The R Journal
R Bloggers Blog
RSeek
R Mailing List Archives
Nabble R
Jeromy Anglim's Blog: Psychology and Statistics

R Graphics

R: Basic Graphs from Quick-R
R: From data to graphics
R Basic Graphs
Graphics by example (UCLA)
GGPLOT2