boostedsignal

You write that the frequentist doesn't answer the question, but it does. It answers: P(H') = (H/H+T)^H'

The question was asking for P(H' | H, T), not P(H').

You also write that the frequentist solution fails to give an error estimate, yet you don't show that the Bayesian solution does give one.

Because there is no error? In the proof I assume P(p) is known and then after that every step follows from a law of probability. There is no error to be accounted for in the procedure. The only caveat is that we need to know P(p) to be able to perform the procedure, which is a caveat that I point out at least 3 times in the page.

Yeah, there are lots of good books out there. My goal was to get the point across in a 5-minute read (give or take).

For those unclear on the concrete (rather than philosophical) difference between Bayesian and frequentist statistics in the first place, I hope it's not inappropriate for me to share this 5-minute example that I wrote a while back: https://news.ycombinator.com/item?id=11096129

How about this! http://www.boostedsignal.com/blog/

Thank you! That was my goal. I banged my head so much against the wall trying to understand the process, even though it should have been conceptually simple. If there are other topics (not necessarily computer-related) that you feel might benefit from a short explanation as well, feel free to let me know, and if I know about them I'd love to write about them.

I wrote a 5-minute tutorial on this (would appreciate feedback): http://www.boostedsignal.com/blog/a28c2988-151e-42cd-b0ab-1c...