1. Consider the joint distribution fXY (x, y) = k · x y (1) over the domain 0 < x < 1, 0 < y < 1, for some k > 0. (a) What value should k have for f to be a proper density? (b) Find the marginal densities of X and Y . Hint: x y = exp[y · log(x)]. (c) Find the mean of Y . (d) Find the conditional mean of Y , given X
1. Consider the joint distribution fXY (x, y) = k · x y (1) over the...
1. The joint probability density function (pdf) of X and Y is given by fxy(x, y) = A (1 – xey, 0<x<1,0 < y < 0 (a) Find the constant A. (b) Find the marginal pdfs of X and Y. (c) Find E(X) and E(Y). (d) Find E(XY). 2. Let X denote the number of times (1, 2, or 3 times) a certain machine malfunctions on any given day. Let Y denote the number of times (1, 2, or 3...
1. Suppose that the joint density of X and Y is given by exp(-y) (1- exp(-x)), if 0 S y,0 syS oo exp(-x) (1- exp(-y)), if 0SyS ,0 oo (e,y)exp(-y) Then . The marginal density of X (and also that of Y), ·The conditional density of Y given X = x and vice versa, Cov(X, Y) . Are X and Y independent? Explain with proper justification. 1. Suppose that the joint density of X and Y is given by exp(-y)...
Please provide correct answer (Very Important) Consider the following joint probability distribution: y fxY (x, y) -1.0 -3 1/8 -0.4 -1 1/4 0. 4 1 1/16 1. 0 3 9/16 Determine the following: (a) Conditional probability distribution of Y given that X = 1 fyll(y) = for y = (b) Conditional probability distribution of X given that Y = 1 fxli (x) = for x = (c) E(X|Y = 1) = (d) Are X and Y independent?
Comparing two densities. Joint density (a) for random variables X and Y is given by: fxy(x, y) = 6e-23-if 0 <y<I<0. Joint density (b) for random variables X and Y is given by: fxY(I, y) = 2e -2- if 0 <1,7 <00. Fill in the following chart and determine whether or not X and Y are independent for both densities (a) and (b). fx() fy(y) EX EY EXY Cou(X,Y) Independent?
1. Suppose that the joint density of X and Y is given by exp(-y) (1- exp(-x)), if 0 S y,0 syS oo exp(-x) (1- exp(-y)), if 0SyS ,0 oo (e,y)exp(-y) Then . The marginal density of X (and also that of Y), ·The conditional density of Y given X = x and vice versa, Cov(X, Y) . Are X and Y independent? Explain with proper justification.
1. (25 points) Consider the following probability density function and the random vector W. fxy(x,y)= 1/16 0 |x|52, lyls2 elsewhere X W=(x,y)" Li a) (5 points) Find and plot the conditional joint probability density function f wilx<0,y>o)(W|x<0, y>0) b) (5 points) Find and plot the conditional joint cumulative distribution function Fw1(x<0,y>0)(W|x<0, y>0) c) (5 points) Find E(W). d) (10 points) Find E(W x<0, y>0).
(1 point) If the joint density function of X and Y is f(x, y) = c(22 - y2)e- with OS: < oo and I y I, find each of the following. (a) The conditional probability density of X given Y = y >0. Conditional density fxy(:, y) = (Enter your answer as a function of I, with y as a parameter.) (b) The conditional probability distribution of Y given X = 2. Conditional distribution Fyx (2) = (Enter your answer...
1. Consider the joint probability density function 0<x<y, 0<y<1, fx.x(x, y) = 0, otherwise. (a) Find the marginal probability density function of Y and identify its distribution. (5 marks (b) Find the conditional probability density function of X given Y=y and hence find the mean and variance of X conditional on Y=y. [7 marks] (c) Use iterated expectation to find the expected value of X [5 marks (d) Use E(XY) and var(XY) from (b) above to find the variance of...
1) Let X and Y have joint pdf: fxy(x,y) = kx(1 – x)y for 0 < x < 1,0 < y< 1 a) Find k. b) Find the joint cdf of X and Y. c) Find the marginal pdf of X and Y. d) Find P(Y < VX) and P(X<Y). e) Find the correlation E(XY) and the covariance COV(X,Y) of X and Y. f) Determine whether X and Y are independent, orthogonal or uncorrelated.
3. Consider the joint probability distribution for Y and X. X/Y 2 4 6 1 0.2 0.21 2 10 201 3 5.2 0 2 a) Calculate the marginal densities for both Y and X. b) Show using the conditional distribution for Y and the marginal distribution for Y, that X and Y are not independent. c) Calculate the E(Y|x = 1)and V(Y | x = 1).