Estimating variance for normal data. Suppose that we observe data X1, . . . , Xn ES N(0, V)we know the mean is 0, but we don't know the variance 1/. (We are writing variance : V, instead of 02, to make it clear that we are working with variance rather than with standard deviation as our parameter.) (a) Calculate the MLE estimate for V as a function of the data X1, . . . , X\". (b) Calculate the Fisher information I02). (0) Calculate the approximate normal distribution of the MLE 13', if the true variance is yo and the sample size n is large. (The mean and variance of the normal may depend on 71 and/or V0, but should not depend on any other quantities.)