3. Let X be a discrete random variable with the probability mass function 2 18 x=1,2,3,4,...
5 Consider a discrete random variable X with the probability mass function rp(x) Consider Y = g( X ) =- 0.2 0.4 0.3 0.1 a) Find the probability distribution of Y. b Find the expected value of Y, E(Y). Does μ Y equal to g(Hy )? 4
5.Consider a discrete random variable X with the probability mass function xp(x) Consider Y-g(X) 0.2 0.4 0.3 0.1 a)Find the probability distribution of Y b) Find the expected value of Y, E(Y) Does μ Y equal to g(μx)? 4
Let X be a discrete random variable with a probability mass function (pmf) of the following quadratic form: p(x) = Cx(5 – x), for x = 1,2,3,4 and C > 0. (a) Find the value of the constant C. (b) Find P(X ≤ 2).
A discrete random variable X has the following probability mass function: p(2) DETİ, for x EA; and zero otherwise. 2 T where C is a constant and A is the support of the distribution. Find the value of C if (c) A 12,3,4,5,...) (a) A (0,2,4,6,.. A discrete random variable X has the following probability mass function: p(2) DETİ, for x EA; and zero otherwise. 2 T where C is a constant and A is the support of the distribution....
Consider a discrete random variable X with the probability mass function p X ( x ) = x/C , x = 3, 4, 5, 6, 7, zero elsewhere. consider Y = g( X ) = 100/(x^2+1) . b) Find the probability distribution of Y.
discrete random variable has probability mass function, P(X = n) = ?1?n. ? 1, forxeven Let Y = −1, for x odd Find the expected value of Y ; (E[y]). probability function mass A discrete random variable has P ( X = n) = (3) for x Y = { for Find the expected value of Y CE(y)] Let even x odd
2. Le X be a continuous random variable with the probability density function x+2 18 -2<x<4, zero otherwise. Find the probability distribution of Y-g(X)- XI
Problem 4 Let X be a discrete random variable with probability mass function fx(x), and let t be a function. Define Y = t(X): that is, Y is the randon variable obtained by applying the function t to the value of X Transforming a random variable in this way is frequently done in statistics. In what follows, let R(X) denote the possible values of X and let R(Y) denote the possible values of To compute E[Y], we could irst find...
2. Le X be a continuous random variable with the probability density function x+2 -2<x<4, zero otherwise. = , Find the probability distribution of Y-g(x)- 12 XI
3. Let X be a discrete random variable with the following PMF: 0.1 for x 0.2 for 0.2 for x=3 Pg(x)=〈 0.1 for x=4 0.25 for x=5 0.15 for x=6 otherwise a) (10 points) Find E[X] b) (10 points) Find Var(X) c) Let Y-* I. (15 points) Find E[Y] II. (15 points) Find Var(Y) X-HX 4. Consider a discrete random variable X with E [X]-4x and Var(X) = σ. Let Y a. (10 points) Find E[Y] b. (20 points) Find...