Generate a chi squared random variable by multiplying the sample variance for each column (of the matrix from Section 2) by . Generate a histogram for this also. Compare this with the theoretical pdf for M-1-4 degrees of freedom chi2pdf (): p(x) = (1/2)/2/2-1-2/2 T(v/2) The way that the var() command works is to take the sum of the squares of the differences from the estimated mean, and divide by M - 1. We cancelled with division by M-1 when we multiplied by (M-1)/o. This generated a chi squared random variable of M-1 degrees of freedom. Also generate a chi squared random variable with M degrees of freedom. This time take the sum of the squares of the differences from the true mean. We then divide by a. Corfipare this with the theoretical pdf for = M = 5 degrees of freedom: 100 am any