![Problem 3 Let A be a random point that coincides with the point a1,a2,as or as with equal probabil- ities. d4 Let a random variable X be the first coordinate of the point A, a random variable Y be the scond coordinate of the point A. (a) Find the joint distribution of random variables X and yY (b) Find the marginal distribution of X and Y. (c) Find the cumulative distribution functions of X and Y (d) Compute E(X] and E (e) Compute Var[X], VarlY], Cor(X, Y), Corr(x, Y). (f) Find the conditional distribution of Y given X =-1,0,1. (g) Compute ElYlXe-1], ElYIX-0), ElYlX = 11. (h) Characterize a random variable E[YJx]. 6) Verify the Law of Iterated Expectations by checking EY]- ELEYIXI G) Is the point with coordinates (EIX], E[Y]) in the support of A? (k) Are the random variables X and Y correlated? Independent? Discuss. (1) What would the joint distribution be if the random variables X and Y are independent and their marginal distributions do not change.](http://img.homeworklib.com/questions/c91f3b40-70a9-11ea-8ba7-83928dc527d5.png?x-oss-process=image/resize,w_560)
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Problem 3 Let A be a "random point" that coincides with the point a1,a2,as or as...
(1 point) 3. Let X and Y be random variables with a joint probability density function...
(1 point) 3. Let X and Y be random variables with a joint probability density function f(z, y)e (a)Find the marginal distribution functions of X and Y, respectively. i.e. Find f(z) and f(y) f(x)- elsewhere (b) Identify the distribution of Y. What is the E(Y) and SD(Y) E(Y)- (c) Are X and Y independent random variables? Show why, or why not (d) Find P(1 X 2|Y 1) E SD(Y)-
Let the frequency function of the joint distribution of the random variables X and Y P(X...
Let the frequency function of the joint distribution of the random variables X and Y P(X = 2, Y = 3) = P(X = 1, Y = 2) = P(X = -1, Y = 1) = P(X = 0, Y = -1) = P(X = -1, Y = -2) = 3 a) Determine the marginal distributions of the random variables X and Y. b) Determine Cov(X,Y) and Corr(X,Y). c) Determine the conditional distributions of the random variable Y as a...
3. In this question, you will identify the distribution of the sum of independent random variables. I expect you wi...
3. In this question, you will identify the distribution of the sum of independent random variables. I expect you will find that the mgf approach is your friend. (a) Let X and Y be independent Poisson random variables with means A1 and 12, respectively, and let S = X+Y. What is the distribution of S? (b) Let X and Y be independent normal random variables with means Husky and variances 07. 07. respectively, and let S = X+Y. What is...
Let the random variable X and Y have the joint probability density function. fxy(x,y) lo, 3....
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).
Problem 1. Let X be a normal random variable with mean 0 and variance 1 and...
Problem 1. Let X be a normal random variable with mean 0 and variance 1 and let Y be uniform(0.1) with X and Y being independent. Let U-X + Y and V = X-Y. For this problem recall the density for a normal random variable is 2πσ2 (a) Find the joint distribution of U and V (b) Find the marginal distributions of U and V (c) Find Cov(U, V).
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let ...
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random variables Z and W (b) Find the density of random variable W (c) Find the density of random variable Z
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random...
Let X be a uniform(0, 1) random variable and let Y be uniform(1,2) with X and...
Let X be a uniform(0, 1) random variable and let Y be uniform(1,2) with X and Y being independent. Let U = X/Y and V = X. (a) Find the joint distribution of U and V . (b) Find the marginal distributions of U.
3. Suppose that Yi and 2 are continuous random variables with joint pdf given by and...
3. Suppose that Yi and 2 are continuous random variables with joint pdf given by and zero otherwise, for some constant c >。 (a) Find the value of c. (b) Are Yi and Y2 independent ? Justify your answer. (c) Let Y = Yi + ½. compute the probability P(Y 3). (d) Let U and V be independent continuous random variables having the same (marginal) distri- 3 MARKS 1 MARK 3 MARKS bution as Y2. Identify the distribution of random...
3. Let the random variables X and Y have the joint probability density function 0 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,...
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).
(1 point) 3. Let X and Y be random variables with a joint probability density function f(z, y)e (a)Find the marginal distribution functions of X and Y, respectively. i.e. Find f(z) and f(y) f(x)- elsewhere (b) Identify the distribution of Y. What is the E(Y) and SD(Y) E(Y)- (c) Are X and Y independent random variables? Show why, or why not (d) Find P(1 X 2|Y 1) E SD(Y)-
Let the frequency function of the joint distribution of the random variables X and Y P(X = 2, Y = 3) = P(X = 1, Y = 2) = P(X = -1, Y = 1) = P(X = 0, Y = -1) = P(X = -1, Y = -2) = 3 a) Determine the marginal distributions of the random variables X and Y. b) Determine Cov(X,Y) and Corr(X,Y). c) Determine the conditional distributions of the random variable Y as a...
3. In this question, you will identify the distribution of the sum of independent random variables. I expect you will find that the mgf approach is your friend. (a) Let X and Y be independent Poisson random variables with means A1 and 12, respectively, and let S = X+Y. What is the distribution of S? (b) Let X and Y be independent normal random variables with means Husky and variances 07. 07. respectively, and let S = X+Y. What is...
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).
Problem 1. Let X be a normal random variable with mean 0 and variance 1 and let Y be uniform(0.1) with X and Y being independent. Let U-X + Y and V = X-Y. For this problem recall the density for a normal random variable is 2πσ2 (a) Find the joint distribution of U and V (b) Find the marginal distributions of U and V (c) Find Cov(U, V).
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random variables Z and W (b) Find the density of random variable W (c) Find the density of random variable Z
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random...
3. Suppose that Yi and 2 are continuous random variables with joint pdf given by and zero otherwise, for some constant c >。 (a) Find the value of c. (b) Are Yi and Y2 independent ? Justify your answer. (c) Let Y = Yi + ½. compute the probability P(Y 3). (d) Let U and V be independent continuous random variables having the same (marginal) distri- 3 MARKS 1 MARK 3 MARKS bution as Y2. Identify the distribution of random...
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).
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