First, find the mean of Y, E(Y): E(Y) = (-1 + 0 + 1 + 2) / 4 = 0.5

Next, compute the variance of Y, Var(Y): E(Y^2) = ((-1)^2 + 0^2 + 1^2 + 2^2) / 4 = (1 + 0 + 1 + 4) / 4 = 1.5 Var(Y) = E(Y^2) - [E(Y)]^2 = 1.5 - (0.5)^2 = 1.5 - 0.25 = 1.25

Since X = 3Y, the covariance of Y and X is: Cov(X, Y) = Cov(3Y, Y) = 3 * Var(Y) = 3 * 1.25 = 3.75