This course is an introduction to R for the complete beginner. My goal is for students to leave the course feeling comfortable enough with R to be able to find solutions for their particular analysis needs.
If you don't already have R installed somewhere, please follow these instructions to do so.
Week 1 (10 September): A first session in R
Week 2 (24 September): RStudio, Project organization and Getting Data into R
Handout for this week--detailed run-down of lecture content with links to all other content for in-class exercises and with the homework assignment. From this handout, you can download everything else you need.
Week 3 (1 October): Importing Data, Objects in R and descriptive statistics
Handout for this week--lecture content with homework assignment. From this handout, you can download everything else you need.
Quick R: Lots of nice information, particularly for users of SAS, SPSS, and Stata. Example-driven approach.
Cookbook for R (formerly R Cookbook): Just as the name suggests, this has contributed "recipes" for analysis. Useful, but you have to do some digging.
R for Matlab users: Nice table of R commands side-by-side with Matlab commands (for those of you coming from a Matlab background).
Google "R cran < topic >"