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3. Let X~ Bin(n,p) with n known (a) State the parameter space for the mode b) State EX] and V[x]. (c) Is p an unbiased estimator for the population proportion p? Show why or why not (d) To estimate the variance of X, we generally use θ 2Pl1 ow is a estimator for V지. (e) Modify 0 from part (b) to form an unbiased estimator for V[X ].

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(a) 1.The Binomial Probability Distribution experiment consists of a sequence of n smaller experiments called trials, where n is fixed in advance of the experiment.

2. Each trial can result in one of the same two possible outcomes.which we denote by success (S) or failure (F).
3. The trials are independent, so that the outcome on any particular trial does not influence the outcome on any other trial.

4. The probability of success is constant from trial to trial (homogeneous trials); we denote this probability by p.

(b) For X ~ Bin(n, p), then E[X]= np, V[X] = np(1 – p) = npq  (where q = 1 – p).

(c) Yes,p hat is an unbiased estimator for population proportion p since the mean of sampling distribution (p hat) is always equal to p

Refer the attached image1 nf In Eummary, w have shenr

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