>> the uncertainty in the number of trials
> Has no meaning to me.
What the author is trying to get at in the admittedly poorly worded question is that the trials are noisy measures of an underlying effect. Your job is to sort by effect size, while accounting for the random chance that a low sample size trial just got unlucky.
You might argue that the question is much harder than the author assumes, since your best guess at the actual effect size seems like it should still just be the success rate, even if the low sample size trials have wider error bars. You'd need to come up with some sort of heuristic that says why 7/9 deserves a lower rank than 50/70 using binomial confidence intervals.
Probably that heuristic is intended to be a bayesian approach? Like, if you add just two successes and two failures to each scenario as a prior, thats enough to put the 50/70 option ahead.
The first question seems a little unfair because it does not say how much more expensive overestimation is compared to underestimation. It implicitly assumes 19:1 given that it's ordering by the 0.05th quantile of the posterior distribution, but that's information not contained in the question.
I don’t know enough about statistics to answer these with math, but I’ve been on quite a few buses and it’s common at some stops for bus arrivals to cluster around specific times. If you always leave after first you see, and most of your random observations are before the first bus, won’t you (almost) always miss the others?
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[ 0.16 ms ] story [ 27.7 ms ] thread>> the uncertainty in the number of trials > Has no meaning to me.
What the author is trying to get at in the admittedly poorly worded question is that the trials are noisy measures of an underlying effect. Your job is to sort by effect size, while accounting for the random chance that a low sample size trial just got unlucky.
You might argue that the question is much harder than the author assumes, since your best guess at the actual effect size seems like it should still just be the success rate, even if the low sample size trials have wider error bars. You'd need to come up with some sort of heuristic that says why 7/9 deserves a lower rank than 50/70 using binomial confidence intervals.
Probably that heuristic is intended to be a bayesian approach? Like, if you add just two successes and two failures to each scenario as a prior, thats enough to put the 50/70 option ahead.