Prove cov(x+y,x-y) where x and y are independent.
5. Prove the following identity: ???(?, ?) = ?(??) − ????, where cov(X,Y) is the covariance between random variable X and Y, ?? is the mean of X and ?? is the mean of Y.
How to prove that: Cov(aX, aY) = a^2Cov(X,Y)
Problem 2 Suppose two continuous random variables (X, Y) ~ f(x,y). (1) Prove E(X +Y) = E(X)+ E(Y). (2) Prove Var(X + Y) = Var(X) + Var(Y)2Cov(X, Y). (3) Prove Cov(X, Y) E(XY)- E(X)E(Y). (4) Prove that if X and Y are independent, i.e., f(x, y) Cov(X, Y) 0. Is the reverse true? (5) Prove Cov (aX b,cY + d) = acCov(X, Y). (6) Prove Cov(X, X) = Var(X) fx (x)fy(y) for any (x,y), then =
Prove the following statements • corr(ax,y) = corr(x,y) • show that if x,y and z are independent. Show what happened to: cov(x+y,x+z)= ? • assume x and y are not independent: cov(ax + b, y)= ? 70 tre la Car
Qs. Random variables X and Y have Joins PDE 0 otherwise (a) What is Cov[X, YT (b) What is Var[X +Y]? (c) Are X and Y independent? Prove your answer. Qs. Random variables X and Y have Joins PDE 0 otherwise (a) What is Cov[X, YT (b) What is Var[X +Y]? (c) Are X and Y independent? Prove your answer.
Let X and Y be two independent random variables. Show that Cov (X, XY) = E(Y) Var(X).
1. Suppose that E(X) E(Y) E(Z) 2 Y and Z are independent, Cov(X, Y) V(X) V(Z) 4, V(Y) = 3 Let U X 3Y +Z and W = 2X + Y + Z 1, and Cov(X, Z) = -1 Compute E(U) and V (U) b. Compute Cov(U, W). а.
4. Recall that the covariance of random variables X, and Y is defined by Cov(X,Y) = E(X - Ex)(Y - EY) (a) (2pt) TRUE or FALSE (circle one). E(XY) 0 implies Cov(X, Y) = 0. (b) (4 pt) a, b, c, d are constants. Mark each correct statement ( ) Cov(aX, cY) = ac Cov(X, Y) ( ) Cor(aX + b, cY + d) = ac Cov(X, Y) + bc Cov(X, Y) + da Cov(X, Y) + bd ( )...
Suppose that Cov(X,Y ) = 0.9 and Cov(X,Z) = −0.7. (a) What is Cov(X,Y + Z)? b) What is Cov(3X,−2Y )?
For independent X and Y, we have probability density function for them where pdf of X is f(x) = ne^-nx and pdf of Y is f(y) = me^-my. (x and y greater than 0). Let M1=max(X,Y) and M2=min(X,Y). Find cov(M2,M1).