It's been a while since my last post, and I hope to get back into regularly posting, now that the semester is starting. I'm also testing out new posting tools.
So, as a beginning, I start with an extract from an introductory statistics class:
I had a strong feeling that this was a job for probability, not for statistics, so I thought, how would one do this problem:
We observe h1=4, N1=10
What is the probability of h2, N2=100?
It seems that the "probability" approach would be more fruitful, so I threw together this little calculation, where I simply marginalize over the single "random coin" parameter, given data 1 (our initial data) and look at the probability of various h2's:!
which also arises in the normalization condition for the beta distribution. This leads to our final solution:
which leads to the following plot, for h1=4, N1=10, and N2=100:
I can't help but think there is a simplification of the equation, but I don't see anything obvious that cancels. Certainly, for large N's I could approximate it.
Anyway, it is clearly a problem for probability not statistics...