These pages provide a few short guides to getting going with R, a free statistical package.

1. Installation.
2. Obtaining a graphical user interface (GUI).
3. At this point, I suggest you read the short guide by Owen (2007), The R Guide, in its entirety. This covers basic data entry, maths, and some statistics.
4. Basics of R objects; entering and manipulating data.
5. Input and output: scripts, saving and loading data (including database access).
6. Basic statistics.
7. Analysis of variance (ANOVA).
8. Basic graphs (1).
9. Basic graphs (2, with ggplot2).
10. Graphs 3: more examples.
11. Handy extensions to R.

Note some general points:

• Use q() to quit.
• Use help.search("keyword") or apropos("keyword") to find stuff in R.
• Use ?keyword for help on a particular topic.
• Use install.packages() to install new R packages (via a graphical interface), or install.packages("package").
• Use functionname (a function name without the usual brackets) to view the source code for a function. If this just shows a UseMethod call (e.g. try this for wilcox.test), then use methods(...) (e.g. methods(wilcox.test) ). That may show you a list of functions, including some non-visible ones. To see their source, use getAnywhere(...) (e.g. wilcox.test.default is listed, so use getAnywhere('wilcox.test.default') ).
• Press CTRL-L to clear the screen.

Typographical conventions used here:

# This is code (stuff you type into R). Hashes (#) indicate comments.

This is output (stuff that R shows you).

/* This is SPSS syntax (stuff you type into SPSS), for comparison to R. */

Other excellent introductions to R on the web include:

• Owen (2007) The R Guide.
• Quick-R (particularly aimed at users migrating from other statistical packages)
• An Introduction to R (from the R web site)
• Faraway JJ (2002) Practical Regression and ANOVA in R.
• Revelle W (2008) Using R for psychological research.
• Baron J & Li Y (2007) Notes on the use of R for psychology experiments and questionnaires.
• William Revelle's short list of the most useful R commands.
• Dong-Yun Kim's Statistical Computing with R: A Tutorial.

For other specific things:

• Glynn EF (2007) Using Color in R

Reference sources (less readable!), include:

• R Data Import/Export (from the R web site)
• The R Language Definition (more technical; from the R web site)
• The full set of R manuals (from the R web site)