It's beginning to look like we don't agree on what Bayesian analysis is. I'm saying that the posterior probability after n tosses updates and supersedes the posterior after k < n tosses. The posterior provides everything that can be known about x, the probability that the coin comes up heads. Bayes can't tell you if the coin is fair; that's for you to decide knowing the posterior. -- Gene From: Warren D Smith <warren.wds@gmail.com> To: math-fun@mailman.xmission.com Sent: Saturday, March 5, 2016 2:12 PM Subject: [math-fun] testing coins (and actresses and bishops?)
From: Eugene Salamin <gene_salamin@yahoo.com>
That's a complete misrepresentation of what I said. The number N of tosses is not fixed.? You can toss all you want, until your decision procedure returns fair, unfair, or undecided.
? --? Gene
--if you, say, apply your test for some N, then 2N, then 4N, then 8N, ... (or maybe N+1, N+2, N+3,...; whatever), until some test says "unfair", then that was not a legitimate testing procedure in the sense that the claimed confidence will be incorrect. Any repeated test whatever, where individual test has confidence C of being right, and you repeat until get some sought result, will no longer have confidence C for that result. Repetition of tests ruins confidences. This is a well known banana peel in statistics. Now you could try to correct for that by altering confidences to try to restore safety, but then you'd be inefficient. Or you could not-do that, in which case you'd be incorrect. So hopefully you now see why I want a procedure designed from the start to involve N continually incrementing, and with confidences correctly based on the failed-termination probability from that whole infinite sequence of experiments.