Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It only takes a minute to sign up.
Sign up to join this community
I have read the wonderful thread entitled Free resources for learning R. The question asks for resources to learn R "on the cheap".
I have a similar question: What is the best and quickest way to learn R, regardless of cost? I am thinking of a week-long intensive course, or similar (could even be much longer). The course would involve learning R from the very beginning and be designed for people with a background in statistics.
Honestly, once you go through the basics, I'd go with a learn-as-you-go approach. When you do a study that requires a certain analysis, then go find a place to learn how to do it. This way, you don't have to worry about forgetting how to code things plus you'll be more motivated to learn about the specific topic. At least that has worked for me so far.
Online courses like Coursera.org has a good selection for statistics using R. For example, this one from Princeton uses R as their teaching software. There are also intensive courses provided by private companies like this one.
Since you mentioned you have statistical background, I believe you also know at least one other statistical software package? If that's the case, I'd recommend first dig out a few comprehensive analyses you have done before, and try to replicate that with R. Through the process, you would need to consult the materials online and get more familiar with the language, and because you have your old output, you can get to compare your results with the model answers. In the process, remember to create and maintain a "cheat sheet" like this PDF document. It'd save a lot of time.
I have been using this language for about 8 years, started with S+. I use it almost everyday but to be frank, I never really endeavored to "learn" R. R is like a giant national park or theme park that you can just take a small chunk in each visit. There are basics like import/export, assigning object, writing function, etc. but then pretty much beyond linear mixed model it's everyone's own game. I hunt for the package that fits my need, and I study the package's manual. And all those basics are generously provided by users online.
