As I’ve spent more time in R, I’ve come to realize the value of a repository of good resources to refer back to when I’m solving a problem. The following is my (growing) list of books and posts I’ve come back to over the years.

Data Science, Programming & R

• I refer back to Hadley Wickham and Garrett Grolemund’s R for Data Science at work and for this blog all the time. As impressed as I was by the text as a master’s student, I am even more impressed by how comprehensive and helpful it is in the “real world”.
• RStudio Cheatsheets are great for quick reference for most major packages.
• R-bloggers is a great way to keep up with what’s going on and learn from other R users.
• Even if computer science is not directly in your domain, Harvard’s CS50 on edX is eye-opening.
• If you’re a beginner and want to get your feet wet and start to develop some muscle memory, DataCamp has some nice courses. I personally think investing time in actual projects is more bang for your buck, but sometimes you just want to do a few coding exercises.
• If you’re doing any kind of data work in R, chances are you’ll want to make tables. Don’t settle for sub-par looking tables. Use the kableExtra package.
• This is more specific to public health, but The Epidemiologist R Handbook is a great reference.

Statistics

• If you’re looking for something not too technical, or you’re just starting out, Discovering Statistics Using R is a highly accessible (and often funny) text to work through.
• If you’re specifically interested in Biostatistics, Fundamentals of Biostatistics is essential reading.

Blogging & Hugo

• Creating Websites with R Markdown is incredibly accessible to beginners and should be a prerequisite for using blogdown.
• Hugo has a huge repository of documents and I’ve been able to answer a lot of my more detailed questions by just typing keywords into the search bar.