It will widen your horizon, they said. And here I was, foolishly thinking I could get away with half-assing statistics during my degree.
It will widen your horizon, they said. And here I was, foolishly thinking I could get away with half-assing statistics during my degree.
My wife did more statistics in her psychology degree than I did in engineering.
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It always got me that the maths I was doing in electrical engineering outclassed what my friend was doing for his astrophysics degree. He was probably at the better university too (Debatable for the subjects in question, but both really good).
Did I need that level of maths? No, but it was compulsory for the first 3 years so not much option.
Because engineering is precise, measurable, and easily reproducible. You should be testing your things in a way that all you need is a simple two-sample Z-test.
Experiments on the humans, on the hand, unfortunately, have been outlawed. So all you get is a bunch of shitty noisy data, and yet you’re supposed to somehow make sense of it. Most people with a degree in stats would tell you not to even try, and yet those fucks at phycology departments always do while having had about one undergrad-level class as part of their masters.
TL;DR good psychology programs nowdays train decent statisticians as they should.
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Engineering formulas be like
“So there was this guy in 1896 and he did a bunch of trials and he figured out that a+b*x/c² is close enough to the real results, with values for a in range 1-2 and b in range 3-4. We still don’t understand why, or how he got there, but it worked ever since.”
Scientists want to understand things. Engineers don’t care, as long as it works.
“More recent research has produced a more precise emperical relation, -4.2x^3.761+√(sin(2x²/π))±erf(e²ˣ+37), which produces results which are 0.2% more accurate on average.”