Let X1, X2,... be a sequence of independent and identically distributed random variables w...

Let X1, X2,... be a sequence of independent and identically distributed random variables with distribution F, having a finite mean and variance. Whereas the central limit theorem states that the distribution of approaches a normal distribution as n goes to infinity, it gives us no information about how large n need be before the normal becomes a good approximation. Whereas in most applications, the approximation yields good results whenever n ≥ 20, and oftentimes for much smaller values of n, how large a value of n is needed depends on the distribution of Xi. Give an example of a distribution F such that the distribution of    is not close to a normal distribution.