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Replying to @peterseibel
@peterseibel I tried to update this to use http://www.evanmiller.org/bayesian-ab-testing.html … as the stopping condition, but empirically still get the peeking problem.3 replies 0 retweets 0 likes -
Replying to @avibryant
@avibryant Hmmmm. I guess one of us three isn't as clever as he thinks he is.1 reply 0 retweets 1 like -
Replying to @peterseibel
@peterseibel@avibryant Using flat priors won't change things much.2 replies 0 retweets 0 likes -
Replying to @venusatuluri
@peterseibel@avibryant actually kinda jumped the gun there. Probably nothing can help when there're egregious stopping rules.1 reply 0 retweets 0 likes -
Replying to @venusatuluri
@venusatuluri@peterseibel yeah, which is fine. But you frequently see assertions that "bayesian exp design doesn't have that problem".1 reply 0 retweets 0 likes -
Replying to @avibryant
@venusatuluri@peterseibel so I'm trying to understand what that actually means, and how I can empirically demonstrate it.2 replies 0 retweets 0 likes -
Replying to @avibryant
@avibryant@peterseibel Rather the point is to estimate the effect size and the uncertainty there, instead of giving a binary decision.1 reply 0 retweets 0 likes -
Replying to @venusatuluri
@venusatuluri@avibryant So how do you run an experiment so you can stop as soon as you reach a certain acceptable level of uncertainty.2 replies 0 retweets 0 likes -
Replying to @peterseibel
@peterseibel@venusatuluri presumably by modeling the EV of doing so, and doing it only when it seems worthwhile.1 reply 0 retweets 0 likes
@peterseibel @venusatuluri ... but really this feels like you will always end up at something like bayesian bandits.
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Replying to @avibryant
@avibryant@peterseibel@venusatuluri Bayesian Bandits is my Crash Bandicoot tribute game.0 replies 0 retweets 0 likesThanks. Twitter will use this to make your timeline better. UndoUndo
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