How to Learn R
R is an open source language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. It has both the flexibility and steep learning curve of a programming language.
Where can I find R?
Since R is freely available, it can be downloaded on any computer. You begin by downloading the base R package from CRAN (The Comprehensive R Archive Network) at http://cran.r-project.org. As R’s capabilities increase through the downloading of additional packages (see any of the resources below for further information about packages), this initial download is very quick.
Many R users recommend supplementing R with RStudio, a free integrated development environment. “RStudio is a set of integrated tools designed to help you be more productive with R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.”
How can I learn R?
An Introduction to R is available from CRAN that gives an overview of the language and guidance on how to use R for doing statistical analysis and graphics. Click “Manuals” on the homepage to find it.
Penn Libraries has constructed this collection of R Resources for both beginners and experienced users.
Some Penn students (depending upon school/program) receive a free Lynda account (must log in with PennKey). Lynda offers professionally made video tutorials on a wide range of subjects. This R Statistics Essential Training tutorial is especially helpful for new users.
Through Coursera, you can take the R Programming course offered by Johns Hopkins, which usually restarts at the beginning of each month. “The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.”
A nice interactive option is available at swirlstats.com. Developed for new users, “SWIRL is a software package for the R programming language that turns the R console into an interactive learning environment. Users receive immediate feedback as they are guided through self-paced lessons in data science and R programming.”
Resources on Campus
The Wharton Public Policy Initiative provides in-person workshops about twice per semester. Beginners can learn how to navigate the software’s interface (using RStudio), computation and syntax, installing and using packages, importing and converting data, and some statistical analysis (i.e., descriptive statistics and regression). This workshop is a great introduction to R and serves as the foundation for future self-study or utilization in a research or professional setting. Some background in statistics is recommended. Check this site often for new workshops or sign up for the Wharton PPI mailing list.