(5 points) Suppose the joint probability mass function (pmf) of integer- Y ī PlX = í,ys j) = (i + 2j)o, for 0 í valued random variables X and < 2,0 < j < 2, and i +j < 3, where c is a con...
(1) Suppose the following is the joint PMF of random variables X and Y P(X x,Y y) c(3x + y), x1,2, y 1,2 where c is an unknown constant a. What is the value of c that makes this a valid joint PMF? b. Find Cov(X, Y)
4. Let X and Y be random variables of the continuous type having the joint pdf f(x,y) = 1, 0<x< /2,0 <y sin . (a) Draw a graph that illustrates the domain of this pdf. (b) Find the marginal pdf of X. (c) Find the marginal pdf of Y. (d) Compute plx. (e) Compute My. (f) Compute oz. (g) Compute oz. (h) Compute Cov(X,Y). (i) Compute p. 6) Determine the equation of the least squares regression line and draw it...
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)
Random variables \(X\) and \(Y\) have joint probability mass function (PMF):\(P_{X, Y}\left(x_{k}, y_{j}\right)=P\left(X=x_{k}, Y=y_{j}\right)= \begin{cases}\frac{1}{20}\left|x_{k}+y_{j}\right|, & x_{k}=-1,0,1 ; y_{j}=-3,0,3 \\ 0, & \text { otherwise }\end{cases}\)(a) Find \(F_{X, Y}(x, y)\), the joint cumulative distribution function (CDF) of \(X\) and \(Y\). A graphical representation is sufficient: probably the best way to do this is to draw the \(x-y\) plane and label different regions with the value of \(F_{X, Y}(x, y)\) in that region.(b) Let \(Z=X^{2}+Y^{2}\). Find the probability mass function (PMF)...
The following table presents the joint probability mass function pmf of variables X and Y 0 2 0.14 0.06 0.21 2 0.09 0.35 0.15 (a) Compute the probability that P(X +Y 3 2) (b) Compute the expected value of the function (X, Y)3 (c) Compute the marginal probability distributions of X and )Y (d) Compute the variances of X and Y (e) Compute the covariance and correlation of X and Y. (f) Are X and Y statistically independent? Clearly prove...
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.
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).
The discrete random variables X and Y take integer values with joint probability distribution given by f (x,y) = a(y−x+1) 0 ≤ x ≤ y ≤ 2 or =0 otherwise, where a is a constant. 1 Tabulate the distribution and show that a = 0.1. 2 Find the marginal distributions of X and Y. 3 Calculate Cov(X,Y). 4 State, giving a reason, whether X and Y are independent. 5 Calculate E(Y|X = 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...
A step by step solution 2. Suppose X and Y are random variables with joint probability density function of the form f(x, y) +y, for 0 S r S 1; and 0 SyS 1 and zero elsewhere. (a) Find the marginal distribution of X and Y. (b) Compute E(X), E(Y); Var(X) and Var(Y). (c) Compute Cov(X, Y). (d) Compute El(2X - Y)