here from above f(x,y) =(e-7*7x/x!)*(e-2*2y/y!) =f(x)*f(y)
therefore x and y follows poisson distribution with parameter 7 and 2.
hence X+Y will follow poisson distribution with parameter 9.
P(X+Y<=3)=
=0.021 option B is correct
Let.X and 7 be random losses with joint density function fr, y- for x and y...
7. Two random variables X and Y have joint probability density function s(x, y) = $(1 – xy), 0<x< l; 0<y<l. The marginal pdfs for X and Y are respectively S(x) = {(2-x) 0<x< 1; s()= (2-y) 0<y<l. Determine the conditional expectation E(Y|X = x) and hence determine E(Y) [7] (ii) [3] Verify your answer to part (i) by calculating the value of E(Y) directly from the marginal pdf for Y. [Total 10]
9. Let the joint density function of (X, Y) be E (0, oo fa,y) ye e forx (O,co) and y (o, co) (a) [4 points] Find fr) and fxy(xly) (b) [3 points] Compute the conditional expectation E(XIY). (c) [3 points] Find P(X > 3Y 1)
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).
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)
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).
Let X and Y be random losses with joint density function and 0 otherwise. An insurance policy is written to reimburse X +Y. Calculate the probability that the reimbursement is less than 1.
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...
Consider random variables X and Y with joint probability density function (Pura s (xy+1) if 0 < x < 2,0 <y S4, fx.x(x, y) = otherwise. These random variables X and Y are used in parts a and b of this problem. a. (8 points) Compute the marginal probability density function (PDF) fx of the random variable X. Make sure to fully specify this function. Explain.
1. a) Let X and Y be random variables with the following joint probability density function (pdf) Зу f(x,y) = 0<y< 2x2,0<x< 1. 2.02 i) Obtain the value for E(Y|X = }). ii) Show the relationship between E[Y|X] and E[XY]. Use this result to obtain E[XY]
em 1. Let X and Y be continuous random variables with joint probability density function y S 2. The two marginal Probl f(z, y) = (1/3)(z + y), fr (zw) in the rectangular region 0 distributions for X and Y are z 1,0 Calculate E(XIY_y) and Var (지Y-y) for each ye[O,2].