There are many possible statistical programs that can be used in psychological research. They differ in multiple ways, at least some of which are ease of use, generality, and cost. Some of the more common packages used are Systat, SPSS, and SAS. These programs have GUIs (Graphical User Interfaces) that are relatively easy to use but that are unique to each package. These programs are also very expensive and limited in what they can do. Although convenient to use, GUI based operations are difficult to discuss in written form. When teaching statistics or communicating results to others, it is helpful to use examples that may be used by others using different computing environments and perhaps using different software. This set of brief notes describes an alternative approach that is widely used by practicing statisticians, the statistical environment R. This is not meant as a user's guide to R, but merely the first step in guiding people to helpful tutorials. I hope that enough information is provided in this brief guide to make the reader want to learn more. (For the impatient, an even briefer guide to analyzing data for personality research is also available.)

It has been claimed that "The statistical programming language and computing environment S has become the de-facto standard among statisticians. The S language has two major implementations: the commercial product S-PLUS, and the free, open-source R. Both are available for Windows and Unix/Linux systems; R, in addition, runs on Macintoshes." From John Fox's short course on S and R.

R project, based upon the S and S+ stats packages, has developed an extremely powerful set of "packages" that operate within one program. Although described as merely "an effective data handling and storage facility [with] a suite of operators for calculations on arrays, in particular, matrices" R is, in fact, a very useful interactive package for data analysis. When compared to most other stats packages used by psychologists, R has at least three compelling advantages: it is free, it runs on multiple platforms (e.g., Windows, Unix, Linux, and Mac OS X and Classic), and combines many of the most useful statistical programs into one quasi integrated program. (R is free software as part of the GNU Project. That is, users are free to use, modify, and distribute the program, within the limits of the GNU non-license). The program itself and detailed installation instructions for Linux, Unix, Windows, and Macs are available through CRAN (Comprehensive R Archive Network).

For a complete look at this issue, see: The Personality Project.