Instructor: Dr. Mario Ventresca,
R is a programming language and environment developed by (mostly) statisticians using the language S as a base. Given its statistical roots, there is no surprise that R is very well suited for performing a variety of statistical, graphical and computational techniques. One major difference from mainstream environments such as Matlab, Maple and Mathematica is that R is open source, which has led to the development of a plethora of libraries to perform just about any analysis task you could consider (regression, classification, clustering, time series, visualizations, data mining, optimization, and so on). As such, the process of analyzing data is likely to be much quicker using R than an alternative environment.
This tutorial will provide you with the basic tools and exposure to R. We will cover a variety of statistical and graphical tools, using practical data analysis examples. Given that the power of R lies largely in the variety of approaches available to you, it is best if you are (at least conceptually) familiar with:
If these topics are unfamiliar I HIGHLY suggest to spend a few minutes on wikipedia looking them up. The tutorial is about R and its uses, not about the statistical procedures being highlighted and therefore these methods will not be explained during tutorial.