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by b10nic
845 days ago
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Not quite; the probability of n/2 successes in n trials is given as Binomial(n,p) not p^n. p^n is correct for a single sequence but there are many possible sequences that result half heads, half tails and so you have a factor of "N choose X" or the so called "Binomial Coefficient". > (0.4)^20 × (0.6)^20 and I think you mean (0.4)^10 × (0.6)^10 or more generally p^x*(1-p)^n-x. |
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The number of heads is a sufficient statistic, so we'll get the same likelihood ratios out, but the likelihood values themselves will be larger.
You could make a similar point about the original CrossValidated Normal(0, 1)^N example by summarizing the data with the mean and sum of squares.
This doesn't work if the data were Cauchy(0, 1)^N instead.