How R you at statistics?

[Disclaimer] This post is little more than an exclamation of science-geek joy at some media attention for the stats program I use. Non-geeks are free to stop reading now, lest you be contaminated. Also, I must apologize that it is a little dated now, the original news item that sparked it having come out 3 weeks ago.

esearch in science invariably includes running statistical tests. The more complicated the experiment, the more complicated the test to determine whether my results are significant. I am delighted that the research community has a tool like R, which in addition to being fully-featured, extensible, and producing pretty figures, is free software (as in free beer, but also as in free speech). There are other tools out there that have comparable features (so I hear, anyway), but as a student I could not have afforded to put them on my personal computer.

So I'm a big fan of R, and am delighted to report that it is gaining headway in my local linguistics department against the old commercial packages.

Imagine my glee, then, to learn that the New York Times published an article earlier this week on the merits of R for data analysis!

Of course, the R discussion lists are all abuzz with the news. People are pleased that it's getting some wider attention, but also (of course) noting the apparent inaccuracies of the piece. None of them are catastrophic, and the writer of the article addresses some of them in his blog follow-up. Which has itself been responded to.

More on R and other free software projects in future posts - for now I'm just enjoying the glow of almost-fame for my little corner of geekdom. Ahhh.