Andrew Gelamn has a nice post on the advantages of knowing more than one statistical programming language.
It's a good point and, at the risk of beating a dead horse, one that I increasingly have taken to heart. I am actually thinking about exposihng my students to R this fall. It's not an ideal choice because I am a mediocre programmer (at best) and I know SAS way better than R. But there is a real push to have our students at least understand Bayesian statistics and I am simply not a fan of the Bayesian approaches in SAS (at least the last time that I looked).
The other reason for teaching R is that it is open source. A corporate license for SAS appears to cost $7000/year. While cheap compared the analyst, it can happen that students will end up in environments where access to SAS isn't easy to obtain and it is nice to have a back-up option.
On the other hand, we often forget the very nice log files and complete outputs that SAS produces. There are environments where a paper trail is essential and SAS is an ideal tool for those cases.
So we'll see how I think about it after this fall but wish me luck!
No comments:
Post a Comment