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The course will make use of three computing environments: Matlab, R and the Gnu Scientific Library. Matlab is a general purpose environment for scientific computing that is particularly strong on matrix methods; it is also good for basic graphics. R was developed for statistical computing and is also very good for the kinds of graphics that arise in statistics. (One of these would suffice, but the course will introduce both so that students are aware of the alternatives for their research.)
Both Matlab and R are high-level environments, and although they can be called from external programs, for getting down and dirty with a large system it can be convenient to have numerical libraries that you can call directly, with a cleanly laid out API. The new Gnu Scientific Library can be very useful for such applications.
For documentation, pointers to tutorials, and other info on using Matlab at CMU, see
http://www-2.cs.cmu.edu/afs/cs.cmu.edu/misc/matlab/common/www/
The entry point to documentation, downloads and information on R is
http://www.R-project.orgYou can run Splus under Andrew, but it is recommended that you simply download R, which is free.
And here is the GSL home page on RedHat (which distributes it):
http://sources.redhat.com/gsl/