This cycle of MITx Courses (Fall) I am taking Data Analysis for Social Scientists. The course covers probability, statistics, and data analysis. It is also conducted in R, so I am now learning R.

I’m still in the early days (first week), but it’s been quite interesting getting exposed to a new programing language. It’s also the first manual programming I’ve done in a while - with all the AI around us. So perhaps a good way to jog my mind-muscles and combat brain rot.

Already one thing I’ve seen about R that is different from the programming languages that I am used to is that the counting starts at 1, rather than the “usual” 0 index counting. I expect there will be more quirks, and perhaps a different way of thinking. (One of the reasons I hear often for learning different languages is that it changes how you think about programming)

I’m complementing the course resources which use a package called swirl with R for Data Science by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund (free online) and R for Beginners by Emmanuel Paradis.

R for Data Science is (from my skimming) very well written, and also, unlike most other programming books, starts with the fun stuff - i.e vizualization - and works back to the dreary routine ones like sourcing data.

I stumbled upon R for Beginners through the R website, and I want to go through it because it’s short, at about 75 pages. I figured that if I read two or so pages a day I would be done in a couple of weeks.

Also while writing this I came across a thread suggesting Hands-on Programming with R by Garett Grolemund (also suggested in the introduction of R for Data Science), so will probably check that out as well.