I have not that much experience with SAS. I first played with it for 6 months several years ago, then again for 3 months a few years ago in very specific jobs (what fun it is to be cleaning data with a pure SAS proc instead of using perl - ouch!)

I have spent much more time with R, but this class is taught with SAS and it objectively shows some advantages that SAS still has today - in the case I was talking about, if you don't want just a log rank test but something more exotic without writing any code, SAS just has it.

Considering how SAS refuses to die, it is interesting to learn with it, before finding a way to do the same in R, as I am likely to encounter some SAS code again!

But in a few weeks, I plan to recode all the examples I see in pure R.

Ugh, I hate SAS. So much of your time spent on SAS is spent on exactly that: the idiosyncracies of SAS (why is input labeled "cards", professor? Oh, because folks have been working on SAS in one way or another since data was still using punch cards...).

R does take more work, but at least it's with generalizable skills. I detest spending my time learning something that can only be used in its narrow niche.

Alternatively, narrow niches offer many other possibilities for selling skills :-)

Fair, but I think "statistician with a strong general programming bsckground" is actually less common than "statistician with a strong SAS background." Its narrow, but common in that niche.

Indeed!

BTW I just submitted a link to show HN how I include SAS code inside Rstudio. It is a bit ugly but it does the job. If you still need to do some SAS it could be helpful to you.