Given random variables X1, X2, Y with E[Y | X1, X2] =
5X1 + X1X2 and E[Y
2
| X1, X2] =
25X2
1X2
2 + 15, find
E[(X1Y + X2)
2
| X1, X2].
Given random variables X1, X2, Y with E[Y | X1, X2] = 5X1 + X1X2 and...
The joint density of random variables X1, X2 is given by fx1,x2 (x1, 2)= 6x1, for 0 < xı < 1, 0 2 <1 - r Let Y X1X2. Find the joint density of Yi and Y2 Х1, Y?
Consider the independent random variables X1, X2, and X3 with - E(X1)=1, Var(X1)=4 - E(X2)=2, SD(X2)=3 - E(X3)=−1, SD(X3)=5 (a) Calculate E(5X1+2). (b) Calculate E(3X1−2X2+X3). (c) Calculate Var(5X1−2X2).
Two independent random variables X1 and X2 both follow UNIF(0, 1). Define Y = e X1X2 . Find the cumulative distribution function (CDF) or the probability density function (pdf) of Y . (You can choose either one).
Suppose X1 and X2 are continuous random variables with join pdf given by f(x1, x2) = 2(x1 + x2) if 0 < x1 < x2 < 1, and zero otherwise. (a) Find P(X2 > 2X1). (b) Find the marginal pdf of X2. (c) Find the conditional pdf of X1 given X2 = x2.
Let X1 d = R(0,1) and X2 d= Bernoulli(1/3) be two independent random variables, define Y := X1 + X2 and U := X1X2. (a) Find the state space of Y and derive the cdf FY and pdf fY of Y . (You may wish to use {X2 = i}, i = 0,1, as a partition and apply the total probability formula.) (b) Compute the mean and variance of Y in two different ways, one is through the pdf of...
Let X1 and X2 be two discrete random variables, where X1 can attain values 1, 2, and 3, and X2 can attain values 2, 3 and 4. The joint probability mass function of these two random variables are given in the table below: X2 X1 2 3 4 1 0.05 0.04 0.06 2 0.1 0.15 0.2 3 0.2 0.1 0.1 a. Find the marginal probability mass functions fX1 (s) and fX2 (t). b. What is the expected values of X1...
Let X1, X2, X3 be independent random variables with E(X1) = 1, E(X2) = 2 and E(X3) = 3. Let Y = 3X1 − 2X2 + X3. Find E(Y ), Var(Y ) in the following examples. X1, X2, X3 are Poisson. [Recall that the variance of Poisson(λ) is λ.] X1, X2, X3 are normal, with respective variances σ12 = 1, σ2 = 3, σ32 = 5. Find P(0 ≤ Y ≤ 5). [Recall that any linear combination of independent normal...
Suppose X1 and X2 are continuous random variables with X1 ~ Unif(0, 1), X2 | X1 = x1 ~ Unif(0, X1) (a) Find the pdf for the joint distribution of X1 and X2 (b) Find the pdf for the marginal distribution of X1 (c) Find the pdf for the marginal distribution of X2 (d) Find the pdf for the conditional distribution of X1 | X2 = x2 (e) Write 1 or 2 sentences explaining how this problem relates to Bayes’...
Let X1 d= R(0,1) and X2 d= Bernoulli(1/3) be two independent random variables, define Y := X1 + X2 and U := X1X2. (a) Find the state space of Y and derive the cdf FY and pdf fY of Y . (You may wish to use {X2 = i}, i = 0,1, as a partition and apply the total probability formula.) (b) Compute the mean and variance of Y in two different ways, one is through the pdf of Y...
O. Let X1 and X2 be two random variables, and let Y = (X1 + X2)2. Suppose that E[Y ] = 25 and that the variance of X1 and X2 are 9 and 16, respectively. O. Let Xi and X2 be two random variables, and let Y = (X1 X2)2. Suppose that and that the variance of X1 and X2 are 9 and 16, respectively E[Y] = 25 (63) Suppose that both X\ and X2 have mean zero. Then the...