Learning R -- is it worth it?

[SocialQuant]

Hi all,

I'm in the process of teaching myself a new stats programming language to add to my resume for applying to grad school. Most people have told me to learn R, which is what I'm leaning towards, but I'm wondering how beneficial learning R is for jobs outside of grad school?

For instance does anyone have any data on salary differences for people in stats/research fields who are proficient in R vs. people who aren't? Or even salary differences for proficiency in R compared to SAS, SPSS, etc.?

[Farge]

The O'Reily 2016 Data Science Salary Survey might have the information you're looking for. You can see the usage of various technologies, as well as salary breakdowns by a bunch of different metrics. With respect R, you can see that it is the second most common technology used by respondents, so it is definitely useful to know outside of school. I think it is also probably the most commonly used language in academia, but, if your school is r-centric, they will almost certainly have some sort of "Introduction to R" class. If you are trying to learn a language *for* grad school, I think you should focus on doing a specific project. An interesting project done in Excel would speak more to your abilities than learning the basics of R/Python/some other language. It would be even better if the project were in a new language.

[cyberwulf]

Being able to write "proficient in R" (or Stata, SAS, etc.) somewhere on your resume will have virtually no impact on your chances of graduate school admission. The reason to learn R (or another language) is to better prepare yourself for graduate coursework or the post-graduation job market. R will definitely be the best prep for graduate work, as virtually all academic departments operate mostly in R. For some industries (like pharma), proficiency in SAS remains a marketable skill.