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- 3) Assume that a random variable X has moment generating function as follows: e' + e²¹ M(t)=4-2e¹ ∞ Calculate the mean and variance of X. for tIf the moment-generating function of X is 2 M(t) = e' + find the mean, variance, and pmf of X. 2tLet X be a Poisson random variable with parameter k. (a) Show that the moment generating function for X is given by ?? (?) = ?^(?(?^?−1)) (b) Show that E(X) = k. (c) Show that Var (X) = k.1. Let the random variable Y have pdf as f(y)A) = e"=e{(e*-1), y>0, A > 0. Show that W = {e* – 1] ~ xỉ or, equivalently, U = e' –1~}X.let x be a random variable with moment generating function Mx(t)=(0.6 + 0.4e^t)^20 then the variance of x isb) A random variable X follows an exponential distribution, X~Exp(0), with parameter 0 > 0. Find the cumulative distribution function (CDF) of X. i) ii) Show that the moment generating function (MGF) of X is M(t) = iii) Use the MGF in (ii) to find the mean and variance of X.Let X be a continuous random variable whose moment generating function is 4x(t) = (5) ³. Find Var (X)3. (a) Let X be a random variable with PDF f(x) = 1 |x|, |x| ≤ 1. Obtain the MGF of X. (b) Find the PDF of a random variable Y with MGF for t0, and My (0) = 1. 2 et My(0) = (^=¹)'.Let N(t) be the percentage of a state population infected with a flu virus on week t of an epidemic. What percentage is likely to be infected in week 4 if N(3) = 8 and N'(3) = 1.2?6. (b)Suppose that X has moment generating function Mx(t) = ( et +) (i) Find the p.m.f. of X. (ii)Find the mean and variance of X.3. Let X and Y be continuous random variables with joint PDF (3x 0s ysxs1 f(x, y) = {* otherwise Determine the correlation of variables X and Y.The moment generating function of the random variable X is given by mX(s) = e2e^(t)−2 and the moment generating function of the random variable Y is mY (s) =(3/4et +1/4)10. If it is assumed that the random variables X and Y are independent, findthe following:(a) E(XY)(b) E[(X − Y )2](c) Var(2X − 3Y)SEE MORE QUESTIONS