PROBLEM 4 Let X be a continuous random variable with the following PDF 6x(1 - 1) if 0 <r<1 fx(x) = o.w. Suppose that we know Y X = ~ Geometric(2). Find the posterior density of X given Y = 2, i.e., fxy (2/2).
sity functions. Exercise 6.46. Let X, Y be independent random variables with density functions fx and fy. Let T- min(X, Y) and V max(X, Y). Use the joint density function fr v from equation (6.31) to compute the marginal density functions fr of T and fv of V
Suppose two continuous random variables X and Y have cumulative distribution functions Fx(x) and Fy(y) respectively. Suppose that Fx(x) > Fy(x) for all x. Indicate whether the following statements are TRUE or FALSE with brief explanation. (a) E(X) > E(Y) (b) The probability density functions fx, fy satisfy fx(x) > fy(x) for all x. (c) P (X = 1) > P (Y = 1)
Let Xi,.,Xn be independent random variables with common probability density f(x) = ה sin(x) , x E [0, π] (a) Assuming EX,] = 2, calculate Var(X). (b) Assuming Var(Xs + + X,) = Var(X) + Var(Xn) and if a, b є R that Var(ax, + b) = a2Var(X), calculate the mean and the variance of Zn, defined [1 as follows: Var(X1+...+ Xn)
2.9.10 Suppose X has density fX(x) = x3/4 for 0 < x < 2, otherwise fx(x) = 0, and Y has density fr (y)-5y4/32 for 0 < y < 2, otherwise fr (y)-0. Assume X and Y are independent, and let Z = X + Y (a) Compute the joint density fx.r(x. y) for all x, y e R (b) Compute the density fz(z) for 2.
2.8.14 Let X and Y have joint density fX,Y (x, y) = (x2 + y)/36 for −2 < x < 1 and 0 < y < 4, otherwise fX,Y (x, y) = 0. (a) Compute the conditional density fY|X (y|x) for all x, y ∈ R1 with fX (x) > 0. (b) Compute the conditional density fX|Y (x|y) for all x, y ∈ R1 with fY (y) > 0. (c) Are X and Y independent? Why or why not?
Let X and Y be independent identically distributed random variables with means µx and µy respectively. Prove the following. a. E [aX + bY] = aµx + bµy for any constants a and b. b. Var[X2] = E[X2] − E[X]2 c. Var [aX] = a2Var [X] for any constant a. d. Assume for this part only that X and Y are not independent. Then Var [X + Y] = Var[X] + Var[Y] + 2(E [XY] − E [X] E[Y]). e....
Problem 4 Suppose X ~N(0, 1) (1) Explain the density of X in terms of diffusion process. (2) Calculate E(X), E(X2), and Var(X). (3) Let Y = μ +ơX. Calculate E(Y) and Var(Y). Find the density of Y. Problem 4 Suppose X ~N(0, 1) (1) Explain the density of X in terms of diffusion process. (2) Calculate E(X), E(X2), and Var(X). (3) Let Y = μ +ơX. Calculate E(Y) and Var(Y). Find the density of Y.
7. Let X be a random variable with distribution function Fx. Let a < b. Consider the following 'truncated' random variable Y: if X < a, if X > b. (a) Find the distribution function of Y in terms of Fx. (It will be a good additional exercise to sketch FY though you don't have to hand it in.) (b) Evaluate the limit lim FY (y) b-00
Suppose X and Y are two continuous random variables with probability density functions: fx(x)1 for 1<x2, fx(x) 0 otherwise, and fr (v) 3e3y for y>0, fr (y) 0 otherwise. a) Suppose X and Y are independent, is Z-X+ Y"memoryless"? Justify your answer. b) Suppose that the conditional expected value satisfies E(Y X)-X. Find Cov0), and El(Y-X) expX)]. Suppose X and Y are two continuous random variables with probability density functions: fx(x)1 for 10, fr (y) 0 otherwise. a) Suppose X...