Chapter 12 Additional R Resources
In this guide I have tried to give you something close to the bare minimum you’d need to understand R and R Studio enough to complete an introductory statistics course. That’s obviously a fine line to walk. In addition, I have tried to be succinct in what I have chosen to cover to make the guide and each of the chapters more appealing and digestible to readers who have plenty of other things on their plate. All of this means there are certainly things you’ll need that aren’t in this guide.
This chapter is a list of resources for self-paced learning of the R environment. For the most part, these resources assume a basic introductory statistics background and little to no computing experience. Resources for more advanced learning are noted as such.
Courses
Hey, it turns out a few people have already done this! The courses on this list range from a couple hours to five or more weeks. I’ll still keep a list of good ones I hear about or ones that aren’t on this list. [LINK 1] [LINK 2]
Swirl Stats: This is an R package that teaches you to use R from within R/R Studio. Highly recommended for first timers. [LINK]
Statistics with R: This is a series of Coursera courses run by faculty at Duke University. Full participation in the courses costs money, but I think you can audit the courses for free (access to materials but no grading or certificate). [LINK]
Data Science: Another Coursera series out of Johns Hopkins. A very popular series of courses but from my understanding it is given at a more advanced level. If you are new to R you may want to start somewhere else and return to this later. [LINK]
R exercises: Not so much a course as a set of practice problems to help understand the inner-workings of R. Not really focused on data analysis, but definitely helpful to understand how R is interpreting your commands. [LINK]
Websites
Getting Started with R: A list of steps and resources put together by RStudio. I haven’t gone through much of it, but my guess is it’s top notch. [LINK]
R Bloggers: Lots of tutorials, updated every day. For those super-new to R, check out the Learn R tab. [LINK]
UCLA’s Institute for Digital Research and Education: Focuses more on how to perform particular analyses using R. [LINK]
R Weekly is a weekly aggregator of R news. It will reference tutorials for new users, and the examples of what some intermediate-to-advanced R programming can do are always interesting. You can sign up to receive updates. [LINK]
YaRrr! The Pirate’s Guide to R: Includes a free pdf book. I haven’t read it, but I’d have to assume it’s entertaining. [LINK]
twotorials.com posts two-minute how-to videos for learning R tasks. [LINK]
aRrgh: a newcomer’s angry guide to R goes through some of the foundations of R, focusing on the frustrations you might come across as a new user. [LINK]
Books
O’Reilly is a publisher with a strong reputation in technical publishing and a number of books focusing on R. Some are more advanced, but the introductory books should be approachable and good references. Many of the books are visually distinctive by using black and white drawings of animals on their covers. [LINK]
The Art of R Programming by Norman Matloff [LINK]
R in Action by Robert Kabacoff [LINK]
R for Everyone by Jared Lander [LINK]
Learning Base R by Lawrence M. Leemis. This book comes recommended for people with a computing background who want to learn R with a focus on R as a programming language. [LINK]
Here’s a list compiled by Liang-Cheng Zhang, which nicely groups books by reader level: [LINK]