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 t is a positive number.
Let X and Y be independent exponential random variables with pa- rameter ? = 1. Given...
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...
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?
2. Suppose X and Y are independent continuous random variables. Show that P(Y < X) = | Fy(x) · fx (x) dx -oo where Fy is the CDF of Y and fx is the PDF of X [hint: P[Y E A] = S.P(Y E A|X = x) · fx(x) dx]. Rewrite the above equation as an expectation of a function of X, i.e. P(Y < X) = Ex[•]. Use the above relation to compute P[Y < X] if X~Exp (2)...
The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random variables Z and W (b) Find the density of random variable W (c) Find the density of random variable Z The random variables X and Y are independent with exponential densities fx (x) = e-"u(x) (a) Let Z = 2X + and w =-. Find the joint density of random...
Exercise 7. Let X and Y be A. independent exponential random variables with a common parameter (1) Find the transform associated with aX +Y, where a is a constant. (2) Use the result of part (1) to find the PDF of aX +Y, for the case where a is positive and different than1 (3) Use the result of part (1) to find the PDF of X-Y. Justify your answers. Exercise 7. Let X and Y be A. independent exponential random...
Problem #5 (20 points) - Quotient of Two Random Variables Suppose that X and Y are independent positive continuous random variables with pdfs fx(x) and fy (y) and suppose that Z = X/Y. Show that the pdf of Z can be computed from the pdfs fx(x) and fy(y), using fz(2) = fx(yz)fy(y)ydy.
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)
Let X and Y be independent normal random variables with parameters E[X] =ux, E[Y] = uy and Var(X) = x, Var(Y) = Oy. Indicate whether each of the following statements is true or false. Notation: fx,y (x, y), fx(x), fy (v) denote the joint and marginal PDFs of X and Y , respectively; $(x) is the CDF of a standard normal random variable with zero mean and unit variance. E[XY]=0
1. Let {y,)%, be a sequence of random variables, and let Y be a random variable on the same sample space. Let A(E) be the event that Y - Y e. It can be shown that a sufficient condition for Y, to converge to Y w.p.1 as n → oo is that for every e0, (a) Let {Xbe independent uniformly distributed random variables on [0, 1] , and let Yn = min (X), , X,). In class, we showed that...
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).