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11 September 2014

Beta Function

How to compute 10dppk(1p)nk without symbol manipulation.

The symbols I used to write it might be a giveaway. We'll imagine throwing a coin and obtaining sequences of head and tail like HTTTTHTHHH This one has probability p5(1p)5. If p is the probability of obtaining H and k is the number of Hs, then the general form is pk(1p)nk. The chances of obtaining some sequence with k Hs is (nk)pk(1p)nk

But, what if we don't know the value of p? Instead, we just have some guess about where its value is. (For example, perhaps we just know it's very likely in [0.4,0.6].) In general, we'd model this with a probability density: We say that value p happens with probability h(p)dp, where the function h(p) is the probability density. Then, to get an expectation for the probability of seeing k Hs, we average over the possible values of p: 10dph(p)(nk)pk(1p)nk The integral is from 0 to 1, because h(p) must be 0 elsewhere; after all, we know that p is a probability.

If we have no idea what value p has, then we should expect to see all values of k with equal probability. The possible values are 0,1,,n, so the probability is 1/(n+1). How do we express in terms of h(p) that we have no idea what value p has? That's right, we simply choose a uniform distribution h(p)=1, to say that we don't prefer one guess over another. Hence, 10dp(nk)pk(1p)nk=1n+1 and 10dppk(1p)nk=1(n+1)(nk)

Sure, this reasoning is fast and loose. Nevertheless, this is what I did when I had to compute the integral, and, because I thought it's kinda cute, I'll probably not forget the trick. If you want a more rigouros derivation, Wikipedia has one.

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