R is both an open source statistical package and it refers to the computer programming language R. You may download and install whichever version you'd like at: http://www.r-project.org/ . As a robust open source community, R has a lot of online and built-in help. For getting it installed, there's an extensive FAQ just for windows & another for Mac users.
There's so much help out there that it can be daunting to know where to start. Here is a PDF, if you'd like a document to get started. (Be sure to check the Appendix on sources of help & documentation.) but I think that this site is even better: <http://www.statmethods.net/> where the author says
"I created this website for experienced users of popular statistical packages such as SAS, SPSS, Stata, and Systat (although current R users should also find it useful). My goal is to help you quickly access this language in your work. "
Also, there was a complaint that R had a file size limitation (based on hardware constraints) and this is no longer an issue.
Help with specific R questions? use http://www.rseek.org (instead of google, for instance.)
If you'd like more direction than this for R, just let me know. And for those of you wondering about what are the stats alternatives on campus, feel free to poke at my data and research methods support site: http://apps.carleton.edu/campus/at/acad_documentation/data/
(note in particular the sortable table on software available at Carleton.) A specific page for R is coming soon.. the information in these pages is being updated whenever I can get to it during break.