Hello,

Actually, the sample variance is

if you divide by 1/(n-1), it's the unbiased estimator for the variance.

For Var(Xi^2), consider the formula of the variance Var(Z)=E(Zē)-[E(Z)]^2

So here, we have Var(Xi^2)=E(Xi^4)-[E(Xi^2)]^2

For E(Xi^4), you'll have to calculate this on your own (using the mgf, or the pdf)

For E(Xi^2), this is just Var(Xi)+[E(Xi)]^2

For Var([X bar]^2), this is complicated, but still can be done.

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But, I feel like you didn't use correctly the formula for the variance... Because Var(X+Y)=Var(X)+Var(Y) if there is independence...