[Fomite]

R is, I think, an interesting language because it's heavily used by people who would not otherwise learn a programming language. If you compare R not with other programming languages, but with other ways of working with statistical data, this makes far more sense. I don't actually "know" SAS in the way I know a programming language - I know the commands I invoke to do what I want it to do.

Similarly, I encounter lots of people using R who don't actually know what a function is, just that lm(x~y) gets them what they want.

[cvwright]

I see this as a failure of our educational system.

Speaking as an academic in CS, it's our job to teach people skills that they need for dealing with computers in the course of their career. The Math department does this for basic calculus and probability; the English department does this for literature and composition.

Why don't more CS departments offer the service courses that scientists and engineers need to really learn how to manipulate their data and make sense of it? At least part of the problem is probably that the other departments won't require their students to take such a course...

[zhte415]

I'm sure there could be a very strong synergy with Economics and Finance. Especially the cross-over from CS to Finance.

[platz]

Remember Javascript before ES5? 99% of "web programmers" didn't know the language either.

[dmichulke]

My personal experience is similar because I know quite a few people in social sciences.

Conceptually, this is similar to rats pulling a lever or monkeys being reinforced to type the right characters. It also explains p-hacking and many other problems of interpretation.

Now one question I always have is - if you consider R just a tool - what is the difference between things I should fully understand (R?) and things I should only know how to use (e.g., my cell phone)?

How can I justify saying that people should understand R while I myself don't understand quite a few aspects of my cell phone?

[simonbyrne]

Also, many people use it only intermittently, maybe once every six months or so when they have some data to look at. Rather than try to relearn the language and its quirks yet again, it's much easier to take what you did last time and tweak it until you get what you need.

[Fomite]

This too. Between collecting data, writing grant proposals, writing papers, etc. I don't spend time day-in, day-out using R.

Often the first hour of that is thinking "Shit, how do I do that again? Has Hadley written a package to do this better by now? What did I do last time - why did I do that last time?"