To help you see what some of the problems with Chetty’s work is, let’s walk through the top and bottom of his new rankings of 2,478 counties. When thinking about Big Data, I’ve long found it extremely useful to look at the highest and lowest examples in detail to see what kind of patterns leap out. It’s extremely easy these days to look up facts about outliers, so more people should do it. This doesn’t seem to be a common practice among academic data analysts, however, who evidently fear contamination by bias and stereotypes. But instead they wind up suffering from ignorance, which is worse.
When thinking about Big Data, I’ve long found it extremely useful to look at the highest and lowest examples in detail to see what kind of patterns leap out.
Those will usually be the least populous counties because statistical fluctuations.
Steve Sailer
Those will usually be the least populous counties because statistical fluctuations.
Well, in Sailer’s examples it wasn’t.
I’m not sure what to make of this quote. It is better to be ignorant than to believe the wrong thing; ignorance is much easier to identify and fix.
Or maybe he’s saying that the fear of contamination is unjustified? That doesn’t seem accurate either.
EDIT: My bad, it’s Steve Sailer, I read the article and of course he was talking about racial bias, not biases generally.