Statistically independent random variables X and Y are defined by Ox=3 , Oy=2 , E[X]=2 and...
Let X, Y be independent random variables with E[X] = E[Y] = 0 and ox = Oy = 5. Then Var(2x+3Y) = 1. True False
Let X, Y be independent random variables with E[X] = E[Y] = 0 and ox = oy = 5. Then Var(2x +3Y) = 1. True False
Let X and Y be two independent random variables such that E(X) = E(Y) = u but og and Oy are unequal. We define another random variable Z as the weighted average of the random variables X and Y, as Z = 0X + (1 - 0)Y where 0 is a scalar and 0 = 0 < 1. 1. Find the expected value of Z , E(Z), as a function of u . 2. Find in terms of Oy and...
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...
Two random variables X and Y have means E[X] = 1 and E[Y] = 0, variances 0x2 = 9 and Oy2 = 4, and a correlation coefficient xx =0.6. New random variables are defined by V = -2X + Y W = 2X + 2Y Find the means of V and W Find the variances of V and W defined in question 3 Find Rww for the variables V and W defined in question 3
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector, 2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
8. Use characteristic functions to show that if statistically independent random variables X and Y are added, where X is Bernoulli(P) and Y is Binomial(n, p), the resulting random variable is Binomial(n +1,p). Hint: when random variables are discrete (like they are in this case), the pdf is made up of weighted impulses. The characteristic function is then very easy to compute. 8. Use characteristic functions to show that if statistically independent random variables X and Y are added, where...
Two statistically independent random variables, X and Y, are uniformly distributed between 0 and 2 and 0 and 4, respectively. Find and sketch (sketch with all necessary details) the pdf of their sum, Z. Use any information you possess to get to the answer as quickly as possible
Let X and Y denote independent random variables with respective probability density functions, f(x) = 2x, 0<x<1 (zero otherwise), and g(y) = 3y2, 0<y<1 (zero otherwise). Let U = min(X,Y), and V = max(X,Y). Find the joint pdf of U and V.
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