"R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files."
This class will make heavy use of the R project for all assignments. It will behoove you to learn it and learn it well. Plus, you'll likely find it useful in your future scientific endeavors. R is powerful, free and there are precompiled binaries available for Windows, Linux, and Mac OS X (see links below).
The binary packages contain both command-line and GUI versions of the program. The GUI is fairly spiffy, but if you want to use emacs instead, you'll probably want to install ESS: Emacs Speaks Statistics (some emacs distributions come prepackaged with this).
If you don't know R and it all seems a bit daunting, don't fret! A tutorial was held on 02/11 and the TAs are here to help. The slides are available here. To properly prepare yourself for the class, the first thing you should do is download and install the program. Familiarize yourself with how to run it. Start working through the Introduction to R (if you actually make it all the way through, you'll be more than prepared). Those of you familiar with Matlab should find transitioning to R fairly easy. But like most systems, the best way to learn is to dive in and start playing around with it. Have fun!