Let X- (Xi, X2,X3) be an absolutely continuous random vector with the joint probability density function...
1. Let X1, X2, X3 be continuous random variables with joint probability density function 00 < Xi < 00,i=1,2,3 Consider the transformation U-X1, V = X , W-XY + X + X (a) Find the joint pdf (probability density function) of U, V and W. (b) Find the marginal pdf of U, and hence find E(U) and Var(U) (c) Find the marginal pdf of W, and hence find E(W) and Var(W) (d) Find the conditional pdf of U given Ww,...
2. Let Xi and X2 be two continuous random variables having the joint probability density 1X2 , for 0, elsewhere. If Y-X? and Y XX find a. the joint pdf of Yǐ and Y, g(n,n), b. the P(Y> Y), c, the marginal pdfs gi (m) and 92(h), d. the conditional pdf h(galn), and e, the E(YSM-m) and E(%)Yi = 1/2).
2. Let X and Y be continuous random variables with joint probability density function fx,y(x,y) 0, otherwise (a) Compute the value of k that will make f(x, y) a legitimate joint probability density function. Use f(x.y) with that value of k as the joint probability density function of X, Y in parts (b),(c).(d),(e (b) Find the probability density functions of X and Y. (c) Find the expected values of X, Y and XY (d) Compute the covariance Cov(X,Y) of X...
Please answer everything and give a detailed answer. Thanks 2. Let (X, Y) be a continuous random vector with probability density function 2xety, if x 2 0 and 1 < y< 0, 2, else. (c) Find the moment generating function of X; using the moment gener-ating function, calculate Var(X2) (d) Calculate Cov(X, Y). Calculate Var(X +Y) and Var(X -Y). Calculate P(XY 2 2XY 2 1) 2. Let (X, Y) be a continuous random vector with probability density function 2xety, if...
3. You may use this fact throughout: For any scalars a, a2,a3 and random variables .X2, X3: (a) If Cov (Xi, X2) Cov (X2, X3)-p, Cov (Xi, X3)-p and Var(X1,2,3, then write the 3 x 3 covariance matrix of the random vector X = (X1,X2,X3). (b) Compute Var(Xi X2+X3) when p 0.6. (e) Mark is interested in forecasting X using the linear predictor &bbX He realizes the forecast error is X - X X bX2 -bX and a great way...
2. The random variables X1, X2 and X3 are independent, with Xi N(0,1), X2 N(1,4) and X3 ~ N(-1.2). Consider the random column vector X-Xi, X2,X3]T. (a) Write X in the form where Z is a vector of iid standard normal random variables, μ is a 3x vector, and B is a 3 × 3 matrix. (b) What is the covariance matrix of X? (c) Determine the expectation of Yi = Xi + X3. (d) Determine the distribution of Y2...
5. Suppose that three random variables Xi, X2, and X3 have a continuous joint distribution with the following p.d.f. (x1+2x2+3z3) and f(1, r2, 3) 0 otherwise. (a) Determine the value of the constant c; (b) Find the marginal joint p.d.f. of Xi and X3; (c) Find P(Xi < 1|X2-2, X3-1)
3. Let the random variables X and Y have the joint probability density function fxr (x, y) = 0 <y<1, 0<xsy otherwise (a) Compute the joint expectation E(XY). (b) Compute the marginal expectations E(X) and E(Y). (c) Compute the covariance Cov(X,Y).
3. Let the random variables X and Y have the joint probability density function 0 y 1, 0 x < y fxy(x, y)y otherwise (a) Compute the joint expectation E(XY) (b) Compute the marginal expectations E(X) and E (Y) (c) Compute the covariance Cov(X, Y)
Let Xi and X2 be two continuous random variables having the joint probability density f,2)10 0, elsewhere. a. the joint pdf o1% and Y2.9(Y1,Y2), b, the P06 > Yi), c. the marginal pdfs gn () and g2(2), d. the conditional pdf h(walvi), and e. the E(Yalki-y) and E(gYi = 1/2).