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).
For independent X and Y, we have probability density function for them where pdf of X...
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).
Let X and Y denote independent random variables with respective probability density functions, f(x) = 2x, 0<x<1 (zero otherwise), and g(y) = 3y2, 0<y<1 (zero otherwise). Let U = min(X,Y), and V = max(X,Y). Find the joint pdf of U and V.
Let the random variables X, Y with joint probability density function (pdf) fxy(z, y) = cry, where 0 < y < z < 2. (a) Find the value of c that makes fx.y (a, y) a valid pdf. (b) Calculate the marginal density functions for X and Y (c) Find the conditional density function of Y X (d) Calculate E(X) and EYIX) (e Show whether X. Y are independent or not.
9 Let X and Y have the joint probability density function f(x, y) ={4x for 。< otherwise a) What is the marginal density function of Y, where nonzero? b)Are X and Y stochastically independent 9 Let X and Y have the joint probability density function f(x, y) ={4x for 。
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...
Let X and Y be independent and identically distributed with marginal probability density function f(a)- 0 otherwise, where 8>0 (a) [6 pts] Use the convolution formula to find the probability density function of X +Y. (b) [6 pts) Find the joint probability density function of U X+Y and V- X+Y
5. Let X and Y have joint probability density function of the form Skxy if 0 < x +y < 1, x > 0 and y > 0, f(x,y)(, y) = { 0 otherwise. (a) What is the value of k? (b) Giving your reasons, state whether X and Y are dependent or independent. (c) Find the marginal probability density functions of X and Y. (d) Calculate E(X) and E(Y). (e) Calculate Cov(X,Y). (f) Find the conditional probability density function...
5. Let X and Y be independent and identically distributed with marginal probability density function İf a> 0, otherwise, e-ea f(a)-( where >0 (a) [6 pts] Use the convolution formula to find the probability density function of X +Y (b) (6 pts) Find the joint probability density function of V= X + Y U=X+Y and 5. Let X and Y be independent and identically distributed with marginal probability density function İf a> 0, otherwise, e-ea f(a)-( where >0 (a) [6...
2. Suppose X and Y are independent random variables with the pdf (probability density func- tion) f(x) e-2 for x > 0. (a) What is the joint probability density function of (X, Y)? (b) Define W-X-Y, Z = Y, then what is the Joint probability density function fw.z(w, z) for (W, Z). (c) Determine the region for (w, z) where fw.z is positive. (d) Calculate the marginal probability density function for W.
2. Suppose X and Y are independent random variables with the pdf (probability density func- tion) f(x)- for x > 0. (a) What is the joint probability density function of (X, Y)? (b) Define W = X-Y, Z = Y, then what is the joint probability density function fw,z(w, z) for (W, Z). (c) Determine the region for (w, z) where fw,z is positive. (d) Calculate the marginal probability density function for W