1. In class, we have discussed the following theorem: "When the domains of r and y...
) Let X, Y be two random variables with the following properties. Y had density function fY (y) = 3y 2 for 0 < y < 1 and zero elsewhere. For 0 < y < 1, given Y = y, X had conditional density function fX|Y (x | y) = 2x y 2 for 0 < x < y and zero elsewhere. (a) Find the joint density function fX,Y . Be precise about where the values (x, y) are non-zero....
4. The random variables X and Y have joint probability density function fx.y(r, y) given by: else (a) Find c (b) Find fx (r) and fr (u), the marginal probability density functions of X and Y, respectively (c) Find fxjy (rly), the conditional probability density function of X given Y. For your limits (which you should not forget!), put y between constant bounds and then give the limits for r in terms of y. (d) Are X and Y independent?...
4.4-2. Let X and Y have the joint pdf f(x, y) r + y, = x + y, (a) Find the marginal pdfs fx(t) and fy (v) and show that f(x,y)关fr (x)fy(y). Thus, X and Y are dependent. (b) Compute (i) μ x, (ii) μ Y. (111) 07, and (iv) 어.
We said in class that two events A and B are indep(ndent if μ(An B) 6. μ(A)a(B). Sinilarly, two random variables X and Y are said to be independent if their joint density fx.y(r,y) can be expressed as the product of the marginal densities fx(x)fv(y). Let X and Y be independent (scalar) random variables, and ZX Y be a new random variable defined as the sum of X and Y. Show that the moment generating function mz(t) of Z is...
0〈z,0〈y Given the following joint distributionfrY(x,y)-, cez+2y else Calculate the following 1. The value of c that makesfxy a proper pdf 2. The marginal distribution function fx(z) 3. The marginal distribution function fy () 4. P(X 1) 7. The random variables X and Y are independent if it is possible to write fxy (x, y) as the product of Íx (x) and fy (y) such that/xy(z, y) = k . Íx (x) . fy(y) for some value of k. Are...
= xe +1),0 x, y < o. 1/(1y)2. 1. Let X, Y be jointly continuous with joint pdf f(x, y) The marginal densities of X, Y are fx(x)= e", fy (y) (a) (2 points) What are fxy(xy) and fyx(ylx)? (b) (3 points) Compute g(y) E(X[Y = y) and h(a) = E(Y|X = x). (c) (3 points) Compute E(XIY) and E(E(X|Y)) (d) (2 points) Check your answer from (c) by using E(X) E(E(XY) and computing E(X) = afx(x)da separately.
1. Let X and Y be two jointly continuous random variables with joint CDF otherwsie a. Find the joint pdf fxy(x, y), marginal pdf (fx(x) and fy()) and cdf (Fx(x) and Fy)) b. Find the conditional pdf fxiy Cr ly c. Find the probability P(X < Y = y) d. Are X and Y independent?
A point (X, Y ) in the Cartesian plane is uniformly distributed within the unit circle if X and Y have joint density Find the marginal densities fX and fY and state whether X and Y are independent or not. Provide a mathematical justification for your answer. 1, 22 + y2 <1, f(x, y) = { 1 0, otherwise.
Question 1. The joint distribution of X and Y is given. Are X and Y independent? fx.y(2, ) X/Y 1 2 3 0.06 0.42 0.12 2 0.04 0.28 0.08 Check all fx,y(2,y) = fx(x)fy(y), are they equal? What you can say about X and Y? Question 2. Consider the following joint PMF 2,y,z fx.y.z(2,y,) 100 1/4 1/4 010 1/4 1/4 001 1/4 1. Find the PMF of (X,Y). 2. Are (X,Y) independent?
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).