Avani (avani) wrote,
Avani
avani

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[Lazyweb] Statistics question

Dear PeopleWhoKnowStatistics.

Say I have a set of continuously arriving outcomes that have 'goodness' ratings attached. I don't know the distribution of said ratings, but I have some idea of the range, and I have a 1-level deep history of past ratings for some of them. I want to know how many outcomes I should wait for before grabbing one and calling it good. In this case, the payoff for picking sooner is fairly high.

I know there is some sort of actual method for this. The problem is sort of akin to Amazon's old Gold Box Model: given a price, you pick it now or you let it go and wait, giving up a known gain for a potential better future deal.

Can anyone tell me what I'm trying to think of here? This is terribly hard to Google search for :-p

Thanks,
-- Avani (proof positive that you can do years of ML without learning basic stats...)

Tags: lazyweb, math, research
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