Interesting tidbit from FiveThirtyEight:
"Sad news for us data nerds: According to respondents of a recently released December YouGov poll, #statistics was ranked the least interesting college major, with 42 percent of adults calling it 'not interesting.' Criminal justice had the lowest percentage of respondents who called it 'not interesting,' at just 18 percent. When respondents were asked which majors they would pick if they were pursuing a college degree today, a plurality (20 percent) chose #computerscience."
The full poll results are here: https://docs.cdn.yougov.com/8nv9pr6ke6/results_College%20Majors.pdf
Almost surely, a lot of those students who think computer science is interesting, but statistics isn't, are planning on careers in "#datascience," #ML / #AI, etc. So here comes yet another generation of computer scientists who will badly reinvent statistics instead of learning the field from the ground up. Great.
@lulu_powerful Yeah. I usually *don't* pick apart the functions unless (a) something doesn't look right and I want to check, (b) I want to implement a faster and/or more stable version, which doesn't happen nearly as often as it used to, or (c) I'm just curious. But knowing that I *can* is reassuring. Not to mention implementing new tests, where I *always* do the math on paper first!
There's already way too much #ML code out there that basically says "this seems to work." My background is about equal parts #biostatistics and software engineering, so I find this just as frustrating as I do the very large amount of statistically sound but *horribly* inefficient and poorly documented code that makes it into the wild.