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- Suppose that two random variables X and Y have the joint PDFfXY(u, v) = {60(u^2)v u ≥ 0, v ≥ 0, and u + v ≤ 1, 0 otherwise.(a) Are X and Y independent?(b) What is the marginal distribution fX(t)?(c) What is Pr[X ≥ Y]? (To set up the right integral, it might help you to draw the rangeof (X, Y) in the uv-plane and identify the region within that range where u ≥ v.)Let X1, X2 denote two independent variables, each with a x^2(2) distribution. Find the joint pdf of Y1=X1 and Y2 = X2+X1. Note that the support of Y1, Y2 is 0<y1<y2<infinity. Also, find the marginal pdf of wach Y1 and Y2. Are Y1 and Y2 independent?Let X,Y ~ U(0,1) be iid. Derive the distribution of Z=X/Y
- For the joint distribution function f(x,y)=2 for x≥0,y≥0,x+y≤1 and 0 otherwise Find the marginal of X and Y. Are X and Y independent? Find E(X )Let X be a r.v. such that E(X2k) = (2k)!/k! , E(X2k+1)=0 . Find the mgf of X and also its ch.f . Then deduce the distribution of X.(a∗ ) Compute P(X = 4, Y = 5). (b∗ ) Compute the marginal pmf’s of X and Y . (c∗ ) Are X and Y independent? Let Z be the minimum of X and Y . Calculate E[Z].
- Let x and y be joint continuous random variable with joint pdf f XY (x, y) = {cx+ 1, x, y ≥ 0, x + y < 10, otherwise1. Find the constant c.2. Find the marginal PDF’S fX (x) and fY (y)3. Find P(Y<2X2)Let X1, . . . , Xn i.i.d. U([θ1, θ2]), i.e., X1, . . . , Xn are independent and follow a uniform distribution on the interval [θ1, θ2] for θ1, θ2 ∈ R and θ1 < θ2. Find an estimator for θ1 and θ2 using the method of moments.Let X1, .... Xn be a random sample from a population with location pdf f(x-Q). Show that the order statistics, T(X1, ...., Xn) = (X(1), ... X(n)) are a sufficient statistics for Q and no further reduction is possible?
- Let x and y be joint continuous random variable with joint pdf f XY (x, y) = { cx+ 1, x, y≥ 0, x+y< 1 0, otherwise 1. Find the constant c. 2. Find the marginal PDF’S fX (x) and fY (y) 3. Find P(Y<2X^2 )Suppose that the random variables X, Y, Z have multivariate PDFfXYZ(x, y, z) = (x + y)e−z for 0 < x < 1, 0 < y < 1, and z > 0. Find (a) fXY(x, y), (b) fYZ(y, z), (c) fZ(z)IF F(x, y) is the value of the joint distribution function of X and Y at (x, y), show that the marginal distribution function of X is given by G(x) = F(x, ∞) for - ∞ <x < ∞ Use this result to find the marginal distribution function of X for the random variable F(x, y) = { (1-e-x2 ) (1- e-y2) for x>0, y> 0 and 0 elsewhere