[alexleavitt]

This is the same in the social sciences. I'm currently a PhD student in one of the top Communication departments in the US, and it's painful to see how far behind in technical skills and tools the curricula are (eg., Excel and SPSS). I've been self-teaching Python, R, and SQL, and extending my knowledge base from simple regression-based stats to data mining and machine learning, to make up for it. Not only does that allow me to work on massive datasets (and push the field forward across methodologies), but it allows me to improve more 'traditional' approaches by sharing data and models (eg., with .R scripts).

[cvet]

I'm in a well regarded sociology department and there's a huge gap between the sociologists who take technical things seriously (programming, stats) and those who don't. People have actually rolled their eyes in classes when we read papers about simulations. I was lucky: we have a core group of students who program and gather data using modern tools, but I gather this is rare both within my discipline and without.

[algebr]

That's a real shame, data science will hopefully cut through the theoretical BS that are the results of so many social science thesis'.

[calcsam]

Quite interesting; I've heard similar things. A good friend of mine, not as math-y as me, was a psychology PhD student in John Bargh's lab in Yale. She ended up getting her doctorate and leaving the field because she didn't want to be the statistics police.