UConn UseRs - An introduction to R
This page is to serve as a resource for the UConn community (especially EEB) to encourage the use of R in data analysis. It is also the resource site for the EEB Short Course in R, entitled "Introduction to R."
The R project for Statistical Computing
R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror (http://cran.r-project.org/mirrors.html).
UConn UseR Group
We also have a google group to facilitate discussions, questions, and anything else that comes to mind. Check it out at: http://groups.google.com/group/UConn-useRs or subscribe by sending an email to UConn-useRs-subscribe@googlegroups.com
Short Course
In the September/October 2008, we'll be offering a short course in R to beginners. The course will be on Fridays from 2-3:30 in TLS 301 from September 5th through October 17th.
The results of the survey to pick a time and of student R-status are here .
Course Resources
The "R for Beginners" book: http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf
The R "Cheat Sheet" (a great resource to print out and keep near the computer) http://cran.r-project.org/doc/contrib/Short-refcard.pdf
Class 1
R Overview Importing/exporting Data Types Read through the description here:
Class 2
Data Manipulation Intro to graphics Intro to statistics Read through the description here:
Class 3
Data manipulation continued (tapply, table, for, if) Jenica Allen's example
Class 4
Intro to modeling Overview of packages Linear models - lm() and anova() Examples by Suegene and Susan
Read through the description here:
Class 5
Advanced programming Writing functions More about loops
Class 6
Spatial data analysis sp class importing spatial data Example by Trina?
Resources
The R Project homepage: http://www.r-project.org/
Resources to help you learn and use R: http://www.ats.ucla.edu/stat/r/
Analysis of Ecological and Environmental Data: http://cran.r-project.org/web/views/Environmetrics.html