Stata is really interesting. The first chapter in my book, “R for Stata Users” talks about all of the similarities between R and Stata. If you’ve been programming in Stata – rather than pointing & clicking on the menus – you should be able to transition to R more easily than a SAS programmer would. As you can see, the use of Stata in scholarly work is growing as rapidly as R, but you’re right, in the corporate world, it’s rare to find a job looking for it. One of the attributes it shares with R is having to store its data in the computer’s main memory. There are a few ways to break that limit in R, but I don’t know offhand if there are similar ways to do that in Stata.

Cheers,

Bob

I came across this article as I’ve slowly slipped into a mild depression (kidding. . . kind of) after I recently graduated with a Masters in Statistics and found that virtually no job advertisement requires STATA, my statistical package of choice. There is some hope, however, as it looks like SAS may be on the decline relative to STATA. *fingers crossed*

]]>I think Python’s an excellent language. However, it’s way behind R in terms of contributed packages. The Julia language has much of Python’s simplicity and consistency, and is much faster. It will be interesting to see how they compete in the future.

Cheers,

Bob

I’ve thought quite a bit about the “language problem” and I think it helps explain the dominance of SPSS. While its language is only usable in English, SPSS uses a graphical user interface that is available in many different languages. So it has the advantage of being easy to use in any popular language. All the programming-based packages like R, SAS & Stata face the same language barrier.

Unfortunately, I’m unaware of any analysis that attempts to quantify this effect, so it’s all just guesswork on my part.

Cheers,

Bob

I’m glad you liked it!

Cheers,

Bob

I really appreciate your scholarly approach to this question.

I have just started introducing R to spanish speakers in Ecuador, many of whom regard it with great suspicion and resent it doubly for being code-based and in english. I am looking for an analysis of the popularity of R amongst its peer programs, considering users with first-languages, or work contexts other than english.

My question is, are you aware of an analysis of this type that adjusts for the language “problem”?

regards,

David