
Ryan S. answered 11/02/13
Tutor
4.8
(10)
Mathematics and Statistics
First notation:
E[X] means the expected value of X and equals the mean of X.
E[X^2] means the expected value of X^2 and can be calculated given the mean and standard deviation of X.
Var(X) = E[X^2] - (E[X])^2 and is equal to the square of the standard deviation of X.
It follows that E[X^2] = (standard deviation of X)^2 + (mean of X)^2
Similar notation and relationships for Y.
We need to assume that X and Y are independent, otherwise we need the Covariance of XY.
Under independence Var (X + Y) = Var(X) + Var(Y).
True for scalars:
Var(aX) = a^2*Var(X)
True for constants:
Var(a+X) = Var (X)
So
Var(2X-4Y+8) = 4*Var(X) + 16 Var(Y). The standard deviation is the square root of the variance.
Expected value or mean is more straight-forward.
E[2X-4Y+8] = 2*E[X] - 4*E[Y] + 8

Ryan S.
11/02/13