Hi all,
A quite stretch for posting on Jason Collins blog, but posts in April and May were:
Explaining base rate neglect: Over the last couple of months I delivered a series of lunchtime seminars at a wealth manager. I botched my explanation of base rate neglect, so wrote this post as a follow up.
Megastudy scepticism: Late last year Katherine Milkman and friends “introduced” us to the megastudy. It landed in Nature with a fair degree of fanfare. My take: a lot to like but “Even in a world of megastudies, we are still in a world of poor theory, questionable generalisability and inadequate statistical power.”
Teaching is over for the semester, so you’ll see an increased flow of posts over the coming month or two.
As always, comments and feedback welcome.
Cheers
Jason
Your examples are nice theoretical illustrations of the effects, on statistical estimates, of failing to take ‘base rates’ into account. However, it seems to me that it w/d be impossible to arrive at rates which were sufficiently relevant/accurate to be applicable in practice. Consider the covid example: It w/d not be feasible to derive a natural frequency (“from observing cases that have been representatively sampled from a population”; or otherwise) that could realistically be applied to a self-selected individual undertaking a RAT test (because: symptoms, close contacts, occupation, location etc). Analogous issues (eg: age, family history, genes, race etc) would likely apply to the breast cancer example.