Lately, across the statistical blogosphere, the repeating discussion of R vs. SAS has started up again. In this series of posts, I’ll offer my opinions of the programs, and supply some information. In this post, I introduce the series and say a little about where I am coming from, so you can see where my opinions come from.
I’m a data analyst/statistician. Mostly, I work with researchers in the social and behavioral sciences, education, and medical fields. I’ve been using SAS for about 15 years and R for about 5, and I use SAS more than R. I am not a programmer.
There are many statistical packages, but there are two (SAS and R) that I use regularly – in fact, I use both every day. I like both. I don’t want to give up either. But they are very different.
Two basic differences between SAS and R
Two uncontroversial differences are:
1. SAS is commercial, R is free.
That is, with SAS, you pay an annual license fee, which varies depending on many factors. R, on the other hand, is free. Anyone can download it. (R is a dialect of S, there is also a commercial version of S – called S plus, but I haven’t used it, and I don’t see it mentioned much; there is also at least one commercial version of R, see the comments.).
2. SAS has tech support, R does not.
This is, of course, related to the first point. One of the things you are paying for with SAS is tech support – available by phone or e-mail. I have found SAS tech support to be among the best of any software I’ve used.
What I plan to cover in future posts
1. Ease of learning
2. Getting help
3. Error messages
5. Available statistics
Request for assistance
This series is really for two groups of people: Those trying to learn a little about these two prominent statistical software packages, and those who already know a lot, but want to discuss things. It might get a bit heated in the latter group – people have strong opinions. Please keep it civil.
If you have particularly good links on any of the above, or ideas for more topics in this series, or anything else you’d like to contribute, let me know.
I plan to search using Google (of course) and also look through both SAS-L and r-help and stackoverflow quite a bit. If there are other good places for me to look, let me know that too.
Specialties: Regression, logistic regression, cluster analysis, statistical graphics, quantile regression.