Earlier quoted context omitted.
That's a nice filter. (Of course, I'm a former mathematician as well.) Here's how I think of it: - the prior odds that you picked the double-headed coin are 1/999. - after seeing ten heads, the posterior odds that you picked the double-headed coin are (2^10)/999 - let's approximate this as 1. (Bayes' theorem usually gets expressed in terms of probabilities, but it's so much simpler in terms of odds.) - so it's roughl…
Can you elaborate on the posterior calculation of (2^10)/999?
(posterior odds) = (prior odds) * (likelihood ratio)
The prior odds are 1/999, so we need to show that the likelihood ratio is 2^10.
The likelihood ratio is the probability of seeing 10 heads from a double-headed coin divided by the probability of seeing 10 heads from a fair coin, which is 1/((1/2)^10) or 2^10.