Wonder if you get any numerical instability here in high dimensions by doing a sum of exponentials? Probably not because they’re Gaussian (no long tails) but after looking at scipy.special.logsumexp [1] I’m a bit wary of sums of exponentials with float32. Would be curious to see if there’s any characterization of this (the cited paper in the article only considers the low dimensional case)

[1] https://docs.scipy.org/doc/scipy/reference/generated/scipy.s...

Could you expand on this? I feel like I get the gist of what you’re saying — that your conditional probability of observing the same effect in non “Finnish twin women” is quite high — but what’s the exact connection to frequentist statistics? Couldn’t find a classical “frequentist fallacy” in a cursory search

Great way to put it

WeWork was publicly traded on the NYSE with ticker WE, it went public via a spac in March 2021

I stand corrected - i only recalled they cancelled their IPO, didn't realize they backdoored via a SPAC.

I feel like you could align a lot of the incentives here with an X cent “line charge” or something similar?

You get 10min, 5min push notifications, then if you aren’t in the store within 1 min of your spot in line being called, you forfeit the X cents. But if you are then they give you a discount on whatever your buy so the “line charge” nets out.

However, I’m not sure if there exists an X such that A) you’ll risk it for the convenience but B) it’s enough to actually compensate the store if you don’t go

(Could be some interesting behavioral econ approaches there, maybe?)

Fun to think about, thanks for sharing!