[tansey]

So true.

PG's articles are generally filled with good intuitive insight. Unfortunately, statistics can be very tricky to turn into folksy wisdom. Rules of thumb like "you need 30 samples before you can say anything" that are derived from the CLT are a good example of ones that work well enough in practice, even if they obscure some underlying subtleties. This article is an example of a rule that sounds simple, but actually has so many asterisks that one would expect it to be mostly useless in practice.

If women are performing better on average, it doesn't mean that you should invest in more women necessarily. What if all the remaining candidates would have a negative mean return? If they included Uber and all of a sudden the women now underperform men, does that mean they're biased against men and they need to invest in less women?

There's just so many statistical fallacies at play here that it's a shame that Jessica, Sam, or Geoff didn't point out that maybe someone with a stats background should read the article first before publishing it.