I am pretty sure this tweet is wrong on two or three levels. Can you find them all? But maybe I am wrong. Thoughts?https://twitter.com/davidshor/status/849316701862862851 …
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5. If not that, the author is either (i) grossly incompetent, or (ii) a hack of the worst kind, blackening the good name of Data. Ugh. /fin
6. DURRRRRRR ignored scaling issues on [2]. Revise to "impossible to interpret practical significance of effect size."
yeah bad tweet. also, trying to imagine a story where higher top marginal rates causally increase gender gap. not easy.
I wouldn't even be surprised if the story turned out to be true, given that unions tend to flatten wage dists. But that's not evidence.
also it would require unions to not have a gender-segregating effect between occupations
impression I've been getting in data sci interviews is econometrics emphasis on interpretation + modeling, even implicit, is a huge asset
this, especially for avoiding stupid pitfalls like the ones above, though also very much in feature engineering
Certainly makes sense! It's not like our stats curriculum is cutting-edge in other aspects
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