Getting SASsy

[This article was first published on Civil Statistician » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Although I am most familiar with R for statistical analysis and programming, I also use a fair amount of SAS at work.

I found it a huge transition at first, but one thing that helped make SAS “click” for me is that it was designed around those (now-ancient) computers that used punch cards. So the DATA step processes one observation at a time, as if you were feeding it punch cards one after another, and never loads the whole dataset into memory at once. I think this is also why many SAS procedures require you to sort your dataset first. It makes some things awkward to do, and often it takes more code than the equivalent in R, but on the other hand it means you can process huge datasets without worrying about whether they will fit into memory. (Well… memory size should be a non-issue for the DATA step, but not for all procedures. We’ve run into serious memory issues on large datasets when using PROC MIXED and PROC MCMC, so using SAS does not guarantee that you never have to fear large data.)

The Little SAS Book (by Delwiche and Slaughter) and Learning SAS by Example (by Cody) are two good resources for learning SAS. If you’re able to take a class directly from the SAS Institute, they tend to be taught well, and you get a book of class notes with a very handy cheat sheet.

To leave a comment for the author, please follow the link and comment on their blog: Civil Statistician » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)