) Let X, Y be two random variables with the following
properties. Y had
density function fY (y) = 3y
2
for 0 < y < 1 and zero elsewhere. For 0 < y < 1, given
Y = y, X
had conditional density function fX|Y (x | y) = 2x
y
2 for 0 < x < y and zero elsewhere.
(a) Find the joint density function fX,Y . Be precise about where
the values (x, y) are non-zero.
Check that the joint density function integrates to 1.
(b) Find the conditional density function of Y given X = x.
) Let X, Y be two random variables with the following properties. Y had density function...
. Let X and Y be two random variables with joint probability density function fx,y(x, y)-cy for 0 x 1 and 0 y 1. (Note: fxy(x,y) = 0 outside this domain ) (a) Find the marginal distribution fx(x). (b) Find the value of constant c, using the fact that fx,y(x, y) dx dy = 1.
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.
5. Let the joint cumulative density function of random variables X and Y be given by for z 0, y >0. (Note: Fxy(x, y)-0 outside this domain.) (a) Find P(X S2,Y (b) Find P(X5). (c) Find P(2 <Y s6). (d) Find the joint probability density function f(x, y). Show that your answer satisfies the S 2). two defining properties of a density. (e) Are X and Y independent? Why or why not?
Problem 8: Let X and Y be continuous random variables. The joint density of X and Y is given by: fxy (x, y)2 if 0 yx< 1. Find the correlation coefficient of X and Y, pxy. Problem 8: Let X and Y be continuous random variables. The joint density of X and Y is given by: fxy (x, y)2 if 0 yx
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)
1. Let X and Y be random variables with joint probability density function flora)-S 1 (2 - xy) for 0 < x < 1, and 0 <y <1 elsewhere Find the conditional probability P(x > ]\Y < ).
Let the random variable X and Y have the joint probability density function. fxy(x,y) lo, 3. Let the random variables X and Y have the joint probability density function fxy(x, y) = 0<y<1, 0<x<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).
(II) Multiple continuous random variables: 8.2 Let X and Y have joint density fXY(x,y) = cx^2y for x and y in the triangle defined by 0 < x < 1, 0 < y < 1, 0 < x + y < 1 and fXY(x,y) = 0 elsewhere. a. What is c? b. What are the marginals fX(x) and fY(y)? c. What are E[X], E[Y], Var[X] and Var[Y]? d. What is E[XY]? Are X and Y independent?
55. Let X and Y be jointly continuous random variables with joint density function fx.y(x,y) be-3y -a < x < 2a, 0) < y < 00, otherwise. Assume that E[XY] = 1/6. (a) Find a and b such that fx,y is a valid joint pdf. You may want to use the fact that du = 1. u 6. и е (b) Find the conditional pdf of X given Y = y where 0 <y < . (c) Find Cov(X,Y). (d)...
Let the joint density function of random variables X and Y be f(x,y) = 8 - x - y) for 0 < x < 2, 2 < y < 4 0 elsewhere Find : (1) P(X + Y <3) (11) P(Y<3 | X>1) (111) Var(Y | x = 1)