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Q2 Suppose X1, X2, ..., Xn are i.i.d. Bernoulli random variables with probability of success p. It is known ΣΧ; is an unbiase

2. Suggest an unbiased estimator for pa. (Hint: use the fact that the sample variance is unbiased for variance.) 3. Show that

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Answer #1

Answer:

X1, X2......Xn ud Bernoulli(p) E(X;) =p V(X;) = p(1-P)

We\ know\ that\ \sum_{i=1}^{n}X_{i}\sim Binomial(n,p)

(2)

We\ know\ that\ T=\sum X_{i}\sim B(n,p)

E(T)+E\left (\sum X_{i} \right )=np

Var(T) + Var (< x; x) = np(1-2)

E(T^{2})=np-np^{2}+n^{2}p^{2}\ \ \ \ \ \ \ \ [\because Var(T)=E(T^{2})-(E(T))^{2}]

E(T^{2}-T)=E(T^{2})-E(T)=np-np^{2}+n^{2}p^{2}-np

  =np^{2}(n-1)

\therefore E\left [ \frac{T^{2}-T}{n(n-1)} \right ]=p^{2}

ie\ \ \frac{T^{2}-T}{n(n-1)}\ is\ an\ ube\ of\ p^{2}

or

\frac{\sum X_{i}[\sum X_{i}-1]}{n(n-1)}\ ube\ of\ p^{2}

(3)

\tilde{p}=\frac{\sum X_{i}+2}{n+4}

E(\hat{p})=\frac{1}{n+4}E\left [ \sum X_{i}+2 \right ]=\frac{1}{n+4}\left [ E\left ( \sum X_{i} \right )+2 \right ]

  =\frac{1}{n+4}(np+2)

  =\frac{np+2}{n+4}

  E(\hat{p})\neq p

\therefore \tilde{p}\ is\ a\ biased\ estimator\ of\ p

(4)

Now\ Var(\tilde{p})=\frac{1}{(n+4)^{2}}Var\left ( \sum X_{i}+2 \right )

  =\frac{Var\left ( \sum X_{i} \right )}{(n+4)^{2}}=\frac{np(1-p)}{(n+4)^{2}}

Var(\hat{p})=Var\left ( \frac{\sum X_{i}}{n} \right )=\frac{1}{n^{2}}Var\left ( \sum X_{i} \right )=\frac{np(1-p)}{n^{2}}

  =\frac{p(1-p)}{n}

Var(\tilde{p})<Var(\hat{p})\ when

\frac{np(1-p)}{(n+4)^{2}}<\frac{p(1-p)}{n}

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