please show steps, thank you
(Sec. 5.2, 00) Suppose X and Y are independent random variables with
E[X] = 6, E[Y ] = −3, Var[X] = 9, and Var[Y ] = 25.
Find:
(a) E[2Y − X]
(b) Var[2Y − X]
(c) Cov[X, Y ]
(d) ρ[X, Y ]
(e) Cov[5X + Y, Y ]
(f) Cov[X, 2Y − X]
please show steps, thank you (Sec. 5.2, 00) Suppose X and Y are independent random variables...
9. Let X and Y be two random variables. Suppose that σ = 4, and σ -9. If we know that the two random variables Z-2X?Y and W = X + Y are independent, find Cov(X, Y) and ρ(X,Y). 10. Let X and Y be bivariate normal random variables with parameters μェー0, σ, 1,Hy- 1, ơv = 2, and ρ = _ .5. Find P(X + 2Y < 3) . Find Cov(X-Y, X + 2Y) 11. Let X and Y...
(Sec. 5.2, 00) Let X and Y be discrete random variable’s with possible values {−1, 1} and {2, 4} respectively, and with joint pmf p(x, y) = 2 / (3x * 2y) for x ∈ {−1, 1}, y ∈ {2, 4} and 0 otherwise. Find: (a) E[X], E[Y ], and E[X + Y ] (b) E[XY ] (c) Cov[X, Y ] (d) Cov[3X + 5, 2 − Y ]
probability course 01) 6 and Let X and Y be two independent random variables. Suppose that we know Var(2X-Y) Var(X+ 2Y) 9, Find Var(X) and Var(Y).
Show steps, thanks ·Additional Problem 13. For random variables X and Y it is given that Ox = 2, ơY = 5, and pxy 3 (a) Find Cov(Xx,y) (b) Var(4X-2Y7 Answers: (a) -. (b) 002 10652 li 3 . Additional Problem 14. Suppose Xi and X2 are independent random variables that have exponential distribution with β 4. (a) Find the covariance and correlation between 5Xi + 3X, and 7Xi-2X. (b) Find Var-5X2-2
4. (Sec. 5.2, 00) Let X and Y be continuous rvs with the joint f(x, y) = 2(x+y), for 0 <y <r <1 and 0 otherwise. (a) Find E(X+Y) and E[X - Y) (b) Find E[XY] (c) Find E[Y|X = x) and E[X Y = y). (d) Find Cov[X,Y]
Let X and Y be two independent random variables. Show that Cov (X, XY) = E(Y) Var(X).
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 =
9. Let X and Y be independent and identically distributed random variables with mean u and variance o. Find the following: (a) E[(x + 2)] (b) Var(3x + 4) (c) E[(X-Y)] (d) Cov{(X + Y), (X - Y)}
1. Suppose you have two random variables, X and Y with joint distribution given by the following tables So, for example, the probability that Y o,x - 0 is 4, and the probability that Y (a) Find the marginal distributions (pmfs) of X and Y, denoted f(x),J(Y). (b) Find the conditional distribution (pmf) of Y give X, denoted f(YX). (c) Find the expected values of X and Y, EX), E(Y). (d) Find the variances of X and Y, Var(X),Var(Y). (e)...
X and Y are random variables (a) Show that E(X)=E(B(X|Y)). (b) If P((X x, Y ) P((X x})P({Y y)) then show that E(XY) = E(X)E(Y), i.e. if two random variables are independent, then show that they are uncorrelated. Is the reverse true? Prove or disprove (c) The moment generating function of a random variable Z is defined as ΨΖφ : Eez) Now if X and Y are independent random variables then show that Also, if ΨΧ(t)-(λ- (d) Show the conditional...