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0 and an Let X1, X2, ..., Xn be a random sample where each X; follows a normal distribution with mean u unknown standard devi

(b) [1 point] If K is a biased estimator for o?, state the function of K that would make it an unbiased estimator for 02. If

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Answer #1

(a)

First we find the expected value of K:
\begin{align*} E(K) &= \alpha \beta \\ &\text{[Using the formula for mean of a Gamma distribution]} \\ &= \frac{n-1}{2}*\frac{2\sigma^2}{n} \\ &= \frac{(n-1)\sigma^2}{n} \end{align*}

Thus, the bias for K is given by:
\begin{align*} \boldsymbol{Bias(K)} &= E(K) - \sigma^2 \\ &= \frac{(n-1)\sigma^2}{n} - \sigma^2 \\ &= \left(\frac{n-1}{n} - 1 \right ) \sigma^2 \\ &= \left(\frac{n-1-n}{n} \right ) \sigma^2 \\ &= \boldsymbol{-\frac{\sigma^2}{n}} \ \ \ \ \ \ \ \ \ \ \ \bf \ \ [ANSWER] \end{align*}

(b)

In part (a), we found that K is a biased estimator for \sigma^2 . Moreover, we found the expected value of K to be:
\begin{align*} & \ \ E(K) &&= \frac{(n-1)}{n}\sigma^2 \\ &\Rightarrow \frac{n}{(n-1)}E(K) &&= \sigma^2 \\ &\Rightarrow E\left(\frac{nK}{(n-1)} \right) &&= \sigma^2 \end{align*}

Thus, we can conclude that the function of K which is an unbiased estimator of \sigma^2 is \bf \frac{nK}{n-1} . [ANSWER]

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