plz help solve this

For a sample of size n, the general linear model for a response Y with an intercept and p explanatory variables X1, X2, . .., X,, can be written in matrix form as Y = XB+6 where Y is the vector of n responses, B is a vector of parameters, X is a matrix containing a column of Is as well as columns of the n observations for all the explanatory variables, and e is a vector of independent normal random variables with mean 0 and variance-covariance matrix ofI. Note that Y, e and 0 are n x 1 matrices. 3 is a (p + 1) x 1 matrix, X is an n x (p + 1) matrix, and I is an n x n matrix. It is stated in the Gauss-Markov Theorem that the least-squares estimator 3 is the minimum variance linear unbiased estimator, Take as known that E = G and Var(3) = o'(X X) 1. Prove the Gauss-Markov Theorem