[sky2224]

> we completely fail at statistics (the MAJORITY of analysis is literally just "here's the delta in the mean of these two samples". If I ever do see people gesturing at actual proper analysis, if prompted they'll always admit "yeah, well, we do come up with a p-value or a confidence interval, but we're pretty sure the way we calculate it is bullshit")

Sort of tangential, but as someone currently taking an intro statistics course and wondering why it's all not really clicking given how easy the material is, this for some reason makes me feel a lot better.

[hansvm]

FWIW, I don't think intro stats is easy the way I normally see it taught. It focuses on formulae, tests, and step-by-step recipes without spending the time to properly develop intuition as to why those work, how they work, which ones you should use in unfamiliar scenarios, how you might find the right thing to do in unfamiliar scenarios, etc.

Pair that with skipping all the important problems (what is randomness, how do you formulate the right questions, how do you set up an experiment capable of collecting data which can actually answer those questions, etc), and it's a recipe for disaster.

It's just an exercise in box-ticking, and some students get lucky with an exceptional teacher, and others are independently able to develop the right instincts when they enter the class with the right background, but it's a disservice to almost everyone else.

[eucyclos]

I found the same when I was taking intro to stats - I did get a much better intuition for what stuff meant after reading 'superforecasting' by tetlock and gardner - I find I'm recommending that book a lot come to think of it.