= Var(X) and σ, 1. Let X and Y be random variables, with μx = E(X), μY = E(Y), Var(Y). (1) If a, b, c and d are fixed real numbers, (a) show Cov (aX + b, cY + d) = ac Cov(X, Y). (b) show Corr(aX + b, cY +d) pxy for a > 0 and c> O
Exercise 1 (1). X, Y are random variables (r.v.) and a,b,c,d are values. Complete the formulas using the expectations E(X), E(Y), variances Var(X), Var(Y) and covariance Cov(X, Y) (a) E(aX c) (b) Var(aX + c (d) Var(aX bY c) (e) The covariance between aX +c and bY +d, that is, Cov(aX +c,bY +d) f) The correlation between X, Y that is, Corr(X,Y (g) The correlation between aX +c and bY +d, that is, Corr(aX + c, bY +d)
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 ( )...
X and z are independent. Var(x)=1 ; Var(z) = sigma ^2. E(z)= 0 and y= ax+b+z I) cov(x,y)= ? ii) corr(x,y)=? dependent Varvane 2.
For a random walk with random starting value, let Y, Yoterter-1e for t > 0, where Yo has a distribution with mean μ0 and variance σό . Suppose fur- ther that Yo, et.., e are independent. (a) Show that E(Y) Ho for all t. (b) Show that Var(,) = tơ24 (c) Show that Cody, Y.) = min(t, s) + 05, , lienee , that cov ( var (it) and (d) Show that Corr(,) = 1 for 0st s s.
1. Let the joint probability (mass) function of X and Y be given by the following: Value of X -1 -1 3/8 1/8 Value of Y1 1/8 3/8 (a) Determine the marginal (b) Determine the conditional distribution of X given Y (c) Are they independent? d) Compute E(X), Var(X), E(Y) and Var(Y). (e) Compute PXY <0) and Ptmax(X,Y) > 0 (f) Compute Elmax(X, Y)] and E(XY) (g) Compute Cov(X,Y) and Corr(X, Y) 1
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 =
1. Su the following to 2 decimal places. nE(X) = 2, Var(X) = 9, E(Y) =0, Var(Y) = 4, and Corr(X,Y) = 0.25. Find a. Var(X +Y) b. Cov(X, X +Y) c. Corr(X+Y,x-Y).
(5) Show Corr(aX + b, cY + d) = Corr(X, Y). Hint: Use results for the covariance and variance.] (5) Show Corr(aX + b, cY + d) = Corr(X, Y). Hint: Use results for the covariance and variance.]
Let f(x, y) 2e-(x+y), x > 0, y > 0. Show that X, Y are independent. What are the marginal PDFS of each?