Professor Norm Matloff
Dept. of Computer Science
University of California at Davis
Davis, CA 95616
R is a wonderful programming language for statistics and data management, used widely in industry, business, government, medicine and so on. And it's free, an open source product. The S language, of which R is essentially an open source version, won the ACM Software System Award in 1998.
R is available for Linux, Windows and Mac systems.
You can download R from its home page.
For Ubuntu Linux or other Debian-related OSs, a more direct method is:
% sudo apt-get install r-base
There is a perception among some that R has a steep learning curve, but I disagree. True, R usage has its advanced aspects, but my recommendation is simply, just get started! Start simple, and then refine gradually.
I'll list a few tutorials below (not necessarily the best, just ones I know of). But first, I wish to make a very important point:
"When in doubt, try it out!" That's a slogan I invented to illustrate the point that R's interactive mode allows you to try your own little experiments, the best way to learn. Keep this in mind when you go through the tutorials listed below and in Google.
Here are some resources that I would recommend for learning R:
There are numerous gentle online tutorials on R, such as:
R syntax is similar to those of C, Python, PERL, etc. don't know these terms) object-oriented and has a functional programming philosophy. Here are some introductions to R from a programming perspective:
One of the most debated topics in R online discussions is that of programming tools for R, of which there are many.