PMean: I want to learn (learn more) about R

I get a lot of questions along the lines of “I want to learn R, can you help me?” or “Where can I learn more about R?” or some other variation. These questions are usually from people who are total beginners or who have just started with R. I don’t have a good answer for them, because learning anything new is hard. But let me try here to outline a few things you can do. Some of these, I have no personal experience with, but have heard recommendations.

I will add links to some of the resources listed below as soon as I can.

Take a class: This is the best way to learn R. Here in Kansas City, we have had a Software Carpentry class on R, that I heard was quite good. I, myself, offered a class through the Department of Biomedical and Health Informatics at UMKC in August 2015 and may offer it again in the future. There are also several MOOCs (Massive Open Online Courses) that are quite good, I’ve been told. In particular, there are a series of classes taught by faculty at Johns Hopkins through Coursera that have been recommended by several of my colleagues.

Join a users group: This is also good. You will see a wide range of talks. The topics may not always be what you’re interested in, and the levels of the talks will vary markedly. But a big advantage of users groups is that you can ask questions of the people who give these talks and start to build a network of colleagues who are all learning R (it is a neverending task, even for those who have used R for many years). There is a group in the Kansas City area, and you can find out more about them at meetup.com.

Explore CRAN: The Comprehensive R archive network has many free resources that are very helpful for beginners. The manuals are well written, especially for beginners. If you want to explore some of the specialized applications in R (e.g., genetics, natural language processing, time series analysis), then a good place to start are the CRAN Task Views.

Explore other Internet resources: There are so many other resources on the Internet that it is hard to list them here. There are lots of R bloggers, though many of them are discussing R at a fairly advanced level. Still, you can often find blog posts that offer beginners insights into some of the many features of R. The UCLA Statistics Department offers a lot of R code that is tied to many basic (and advanced) statistics textbooks.

swirl: A lot of my colleagues have been mentioning swirl, an interactive program that teaches you R from within R.

Books: There are lots of good books for R, and many of them are written for beginners. I hesitate to recommend a book, because I have not read any of them. Go to Amazon, and type R software for beginners in the search box to get some recommendations