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3. Suppose you have X Binom(n, p) where n is known and p is unknown. Typically, people use p = _ to estimate p, where X = Xi is simply a sample of size l. This might represent simultaneously flipping n coins (just once!) and counting the number of heads you see, where each coin has Pheads - p. Now, if both n and p are known, we know the variance V of X is just np(1-p) If p is unknown, you might want to estimate V using the estimator ỹ = n( 식 ) ( 1 Find the bias of V, and if it is biased, determine if it is asymptotically unbiased, and also modify X1 X1 V to create a new unbiased estimator.

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3. Suppose you have X Binom(n, p) where n is known and p is unknown. Typically,...
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