R - JasonLocklin/jasonlocklin.github.com GitHub Wiki

R Resources

R is a Free and Open Source implementation of the "S" programming language for statistics. It runs interactively, or can run scripts. Most new users seem to be starting with the RStudio user interface. It provides a script editor, help viewer, interactive terminal and a few other features all-in-one. It is not necessary, but makes things easier and more integrated. R can pull packages of code, data, and documentation from a colossal online repository called "CRAN." Over it's many years, it has accumulated packages for virtually every imaginable task, so having good resources that can point a user in the right direction in order to find what he or she needs is important. What follows is a list of the various online resources that I have found helpful.

Getting started with R and Statistics

• [UCLA Institute for Digital Research and Education] (http://statistics.ats.ucla.edu/stat/r/)

Quick Reference

• R Python Cheatsheet (my cheat sheet here)
• One Page R: A Survival Guide to Data Science with R
• R reference card
• Mathesaurus. Thesaurus-like reference cards for those transitioning between R, Python(numpy), Matlab/Octave, and Scilab.

"Official" Sources

• homepage,
• manuals,
• FAQ, and
• wiki.

Searching for answers

• Rseek search engine.
• Some of the other resources here have integrated search engines, like Stack Overflow, but most, like the mailing list and quick-r, are indexed by Rseek. So start there.

Asking Questions

• R Mailing list (Very high volume email list).
• Twitter: #rstats
• #R IRC chatroom on Freenode.net. If you don't have an IRC client, you can use the web based one here.
• Stack Overflow
• Reddit /r/rstats

Books

• Venables & Ripley, Modern Applied Statistics with S. (note: S is the language that the R project implements)
• R for SAS and SPSS Users. Available as a document, or a complete book.
• Introductory Statistics with R. available online with UW library access
• R in Action, Second Edition. Robert Kabacoff
• Using R for Introductory Statistics, Second Edition. John Verzani. First edition can be downloaded as ebook for free. Second may be available. amazon link.
• Discovering Statistics Using R. Field et al. amazon link
• Lattice: Multivariate Data Visualization with R. amazon. available online with UW library access

Not R-specific:

• Milliken & Johnson, Analysis of Messy Data.
• Huff, How to Lie With Statistics.

Note: R is a Free implementation of the language S. S-plus is a proprietary application that implements S. Most published books will be for S and S-plus, but often have footnotes whenever S and R differ.

Articles

• Linear Mixed Models

Blogs

• R Bloggers: An aggregate of many people's blogs about using R

Tutorials

• An Introduction to R
• Quick-R. A collection of many short and simple tutorials for various tasks in R.
• R Tutorial: Study statistics with R
• Video tutorials here.

Other Lists of resources like this one

• Help for R: A language and environment for statistical computing and graphics

Courses

• DataCamp
• Data Science (Coursera)

Psychology Specific

• Using R for psychological research. A simple guide to an elegant package
• Notes on the use of R for psychology experiments and questionnaires

Category Specific:

Data Management

• Reshape2. Reshape exists in the package repositories for legacy purposes only. Don't start with it, use Reshape2 instead. Don't use apply, sapply, stack, etc. Use either Reshape2 or Plyr to reformat data.
• Plyr and Reshape2 are by the same author, and serve similar functions, so it's a bit confusing as to which to use when.
• Dplyr is the "next iteration" of Plyr, focusing on data frames. See this tutorial

User Interfaces

• RStudio, an elegant graphical interface for Mac/Windows/Linux. It lacks extensive menus, but provides a simple interface to the shell, syntax files, help files, and packages. It also simplifies figure generation and export.
• R Commander, a simple graphical interface that runs as a package within R, so is very easy to install. It is designed with teaching statistics in mind, so provides plenty of menu driven items for simple statistical tasks. -* Emacs Speaks Statistics (for "power users"), a way to interact with R and save transcripts, all within the Emacs text/code editor.

Visualization and misc.

• ggplot2, another graphing package
• rgl, a package for 3D data visualization
• rggobi, another package for 3D data visualization
• singlecase, implements the Crawford t-test and other statistics for comparing a single case to a group of controls. I have some notes on Crawford_tests