These are some useful resources on the web for learning R. Feel free to suggest other resources by clicking the “Improve this page” button in the top right.
- R for Data Science. Book by Garrett Grolemund and Hadley Wickham
- Quick-R. Kabakoff’s website. Great reference along with his book, R in Action.
- O’Reilly Try R. Great tutorial on R where you can try R commands directly from the web browser.
- R Reference Card
- Video Overview of RStudio
- Journal of Statistical Software
- The R Journal
- An Introduction to Statistical Learning with Applications in R
Learning R Markdown
- Video on RMarkdown by RStudio - This 26 minute video talks about some updates to RMarkdown.
- Markdown Basics. Markdown is a way of formatting plain text documents mostly for the web. However, it has become for other writing tasks too. It has become popular because it focusses on writing and not formatting. The formatting is taken care later. The Markdown Basics provides a nice introduction to Markdown.
- The R Markdown Website has a nice introduction on how Markdown is extended to allow for the inclusion of R code and output.
- Video Introduction to R Markdown. This short video (under 4 minutes) was recorded with an older version, so not all of the features and dialog boxes will look the same, but may be helpful.
Data scientists, statisticians, and generally interesting people.
- Hadley Wickham @hadleywickham
- Chris Albon @chrisalbon
- David Smith @revodavid
- Alex Hayes @alexpghayes
- Max Kuhn @topepos
- Daniela Witten @daniela_witten
- Dianne Cook @visnut
- Mara Averick @dataandme
- Angela Bassa @AngeBassa
- Julia Silge @juliasilge
- Frank Harrell @f2harrell
- Joe Cheng @jcheng
- Amelia McNamara @AmeliaMN
- Jenny Bryan @JennyBryan
- Elizabeth Stuart @lizstuartdc
- David Robinson @drob
- Gary King @kinggary
- Rasmus Bååth @rabaath
- Mine CetinkayaRundel @minebocek
- Karl Browman @kwbroman
- Andrew Gelman @statmodeling