I currently have a text book problem that I cant seem to work out:

Suppose X_{1},...,X_{n}~Exp(c) and consider the estimate of the variance sigmahat^{2}(X_{1},...,X_{n})=1/n [n][/i=1] (X_{i}-Xbar)^{2}. Assume c is known.

For c=2, n=10 determine a Monte Carlo (MC) estimate of the bias of sigmahat^{2}. Carefully choose the MC sample size N such that the error of the estimate is small compared to the result.

Also, write an algorithm for given c and n that first determines an appropriate N for the estimate of the bias of sigmahat^{2}and then uses this to compute a good estimate of the bias.

Any help would be greatly appreciated!