How to Use these Resources
The resources below offer tutorials and references for learning R programming and using in different computing and data science contexts. Many are targeted at social scientists, but some are intended for broader audiences.
RStudio Learning Resources -- the makers of RStudio offer a series of online multimedia materials (video, documents, code examples, etc) to help learn R, from beginner-level introduction to the language to more advanced applications of R.
- RStudio Primers -- a series of interactive tutorials (with video, written materials, code examples, etc) covering a range of topics from R basics to using R for data analysis or for visualization.
- RStudio Webinars -- upcoming and archived (recorded) webinars on a range of R topics.
RStudio Essentials -- shorter video tutorials on a bevy of core R topics, from debugging to parallel programming in R
A Gentle Introduction to Tidy Statistics in R -- a ~1-hour webinar (with downloadable slides) on data analysis with R. From the makers of RStudio.
Self-paced online courses
Code Clinic for R -- a self-paced online video course in R programming, with an emphasis on applications to data analysis. Comes with downloadable exercise files and sample code. From LinkedIn Learning, available for free with an active Princeton NetID.
Introduction to R -- self-paced online course from the Cornell University Center for Advanced Computing (CAC) geared at computational scientists and engineers
Web pages / written online tutorials
R resources for every level --- a meta resource with links to additional learning resources for R programming, IDEs, data analysis and visualization with R, etc.
Impatient R -- a detailed no-nonsense tutorial for R beginners, from the author of the "The R Inferno"
R Tutorials -- a compendium of bite-sized tutorials on different R topics from the Association for Computing Machinery (ACM). New posts appear (and are archived) fairly regularly.
Data Analysis with R -- links to slides and exercise materials from a 2012 workshop on R run by the Oak Ridge Leadership Computing Facility (OLCF)
R Cookbook -- link is to the free HMTL version of the 2nd edition. An alternate online version from O'Reilly books is available from Princeton University Library for free to those with an active NetID.
R for Data Science -- a free online version of the popular O'Reilly book by Hadley Wickham.
Advanced R -- another popular book by Hadley Wickham. Link is to a free online version of the second edition.
An Introduction to R (2020) -- a comprehensive textbook for beginners and reference for more advanced users. An online PDF book from the Comprehensive R Archive Network (CRAN) that is regularly updated.