Theorem 2.3.4 : If X is a r.v. with finite variance, then for any constants a and b, Var(aX + b) = a2 Var(X) . Var (X ) = E(X - E(X ) ) 2 (Try ) E(X2) - (E(X) )2 Definition 2.3.6 : Let X be a r.v. with cdf FX. The moment generating function(mgf) of X, denoted by Mx (t), is Setx fx (x) dx if X is continuous Mx (t ) = E(etx ) = Ex ex P(X = x) if X is discrete