4 Show that the following functions are possible joint pdf’s:
(a) f(x, y) = e^−y , 0 ≤ x ≤ y < ∞
(b) f(x, y) = 1/(x^2y^2 ), x, y ≥ 1
4 Show that the following functions are possible joint pdf’s: (a) f(x, y) = e^−y ,...
1. given the joint p.d.f f (x,y)= 2, 0 <x <y <1. 2. show that fx (x)=2(1- x), 0 <x <1 and fy (y)=2y, 0 <y <1 3. show that p(3/4<y<7/8 I x=1/4)=1/6
The joint probability density function of the random variables X, Y, and Z is (e-(x+y+z) f(x, y, z) 0 < x, 0 < y, 0 <z elsewhere (a) (3 pts) Verify that the joint density function is a valid density function. (b) (3 pts) Find the joint marginal density function of X and Y alone (by integrating over 2). (C) (4 pts) Find the marginal density functions for X and Y. (d) (3 pts) What are P(1 < X <...
4. Let X and Y be continuous random variables with joint density function f(x, y) = { 4x for 0 <x<ys1 otherwise (a) Find the marginal density functions of X and Y, g(x) and h(y), respectively. (b) What are E[X], E[Y], and E[XY]? Find the value of Cov[X, Y]
Let X and Y have the following joint distribution X/Y 0 1 0 0.4 0.1 1 0.1 0.1 2 0.1 0.2 a) Find Cov(4+2X, 3-2Y) b) Let Z = 3X-2Y+2 Find E[Z] and σ 2Z c) Calculate the correlation coefficient between X and Y. What does this suggest about the relationship between X and Y? d) Show that for two nonzero constants a and b Cov(X+a, Y+b) = Cov(X,Y)
An insurance policy covers losses X and Y which have joint density function 24y f(x,y) , y>0. (a) Find the expected value of X (b) Find the probability of a payout if the policy pays X + 2Y subject to a deductible of 1 on X and 1 on 2Y. (c) Find the probability of a payout if the policy pays X +2Y subject to a deductible of 2 on the total payment X + 2Y
An insurance policy covers...
1. Suppose the joint density of X and Y is given by f(x,y) = 6e-3x-2y, if 0 < x < inf., 0 < y < inf, 0 elsewhere. Part A, Find P( X < 2Y) Part B, Find Cov(X,Y) Part C, Suppose X and Y have joint density given by f(x,y) = 24xy, when 0<= x <=1, 0 <= y <=1, 0 <= x+y <=1, and 0 elsewhere. Are X and Y independent or dependent random variables? why?
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 have joint density f(x, y) = e−y 1[0 < x < y] Show that Y and X/Y are independent.
Let X and Y have the joint pdf f(x,y) = e-x-y I(x > 0,y > 0). a. What are the marginal pdfs of X and Y ? Are X and Y independent? Why? b. Please calculate the cumulative distribution functions for X and Y, that is, find F(x) and F(y). c. Let Z = max(X,Y), please compute P(Z ≤ a) = P(max(X,Y) ≤ a) for a > 0. Then compute the pdf of Z.
The joint density function for X and Y is given as: f(x, y) = kxy for 0 < x < 2y < 1. Find the value of the constant k for which the p.d.f is legitimate. If the video does not work, click here to go to YouTube directly.