The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let ...
12. Let X and Y be independent random variables, where X has a uniform distribution on the interval (0,1/2), and Y has an exponential distribution with parameter = 1. (Remember to justify all of your answers.) (a) What is the joint distribution of X and Y? (b) What is P{(x > 0.25) U (Y > 0.25)}? (c) What is the conditional distribution of X. given that Y - 3? (d) What is Var(Y - E[2X] + 3)? (e) What is...
Let X and Y be independent exponential random variables with pdfs f(x) = λe-λx (x > 0) and f(y) = µe-µy (y > 0) respectively. (i) Let Z = min(X, Y ). Find f(z), E(Z), and Var(Z). (ii) Let W = max(X, Y ). Find f(w) (it is not an exponential pdf). (iii) Find E(W) (there are two methods - one does not require further integration). (iv) Find Cov(Z,W). (v) Find Var(W).
Let X and Y be two independent random variables such that E(X) = E(Y) = u but og and Oy are unequal. We define another random variable Z as the weighted average of the random variables X and Y, as Z = 0X + (1 - 0)Y where 0 is a scalar and 0 = 0 < 1. 1. Find the expected value of Z , E(Z), as a function of u . 2. Find in terms of Oy and...
7. Let X and Y be independent Gaussian random variables with identical densities N(0,1). Compute the conditional density of the random variable of X given that the sum Z = X + Y is known (i.e., XIX + Y)
Let X and Y be independent exponential random variables with parameter 1. Find the joint PDF of U and V. U = X + Y and V = X/(X + Y)
4. Let X and Y be independent exponential random variables with pa- rameter ? 1. Given that X and Y are independent, their joint pdf is given by the product of the individual pdfs of X and Y, that is, fxy(x,y) = fx(x)fy(y) The joint pdf is defined over the same set of r-values and y-values that the individual pdfs were defined for. Using this information, calculate P(X - Y < t) where you can assume t is a positive...
Let X and Y be independent exponential random variables with pa- rameter ? = 1. Given that X and Y are independent, their joint pdf is given by the product of the individual pdfs of X and Y , that is, fX,Y(x, y) = fX(x) fY(y). The joint pdf is defined over the same set of x-values and y-values that the individual pdfs were defined for. Using this information, calculate P (X ? Y ? 2) where you can assume...
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?
(6 points) Let X and Y be independent random variables with p.d.f.s fx(x) -{ { 1-22 0, for |2|<1, otherwise. fy(y) = for y>0, otherwise. 0, Let W = XY (a) (2 points) Find the p.d.f. of W, fw(w). (b) (2 points) Find the moment generating function of W2, Mw?(t) = E (e«w?). (c) (2 points) Find the conditional expectation of W given Y = y, E(W|Y = y).
I need help on 6.26 and 6.28 please! 6.26 Three independent continuous random variables X, Y, and Z are -uniformly distributed between 0 and 1 . Ifthe random variable S X+ Y+Z, determine the PDF of S. Suppose X and Y are two continuous random variables with the joint PDF fxr(x,y). Let the functions U and Wbe defined as follows: U w=X +2Y. Find the joint PDF fuwlu,w) 6.27 2X+3Y, and 6.28 Find fuw(u, w) in terms of fxrtx,y) if...