R (Tutorials and Readings)
Introduction to R
R is an open source (FREE) program for statistical computing and graphics. It was developed from the S language by John Chambers and colleagues and is very similar to a commercial statistics package called S-Plus. Because R is free and available for all major platforms (mac, pc, linux), learning R means learning a main-stream software package that you can install at home or at work.
R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Here are only two examples of the amazing graphical abilities R has:
(Graphs provided by: http//addictedtor.free.fr/graphiques)
R is command-line driven which means that many of the commands must be entered from the keyboard or typed in a text file and accessed. The advantage of this is that it is very flexible to add different options to a command. The disadvantage is that it takes a little time to learn the commands. Luckily, many of the commands in R are intuitive and there is a graphical user interface (GUI) called R-commander that can be installed from within R (it’s installed by default in the CAL).
To get general information about what R has to offer you go to their website: http://www.r-project.org/
R Installation Guide
R Installation Guide – Windows
R Installation Guide – MAC
R Readings and Tutorials
R Reference Card
R for Beginners
Data Analysis and Graphics
Practical Regression and ANOVA
Ecology and Epidemiology in R (online)