Use the moment generating function technique to solve. Let X1, . . . , Xn be independent random variables, such that Xi ∼ Exponential(θ), for i =1, . . . , n. Find the distribution of Y = X1 + · · · + Xn.
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Use the moment generating
Let X1, . . . , Xn be independent random variables, such that Xi ∼ Exponential(θ), for i =1, . . . , n.
Find the distribution of Y = X1 + · · · + Xn.
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- Use the moment generating function to solve. Let X1, . . . , Xn be independent random variables, such that Xi ∼ Poiss(λi), for i = 1, . . . , n.Find the distribution of Y = X1 + · · · + Xn.Solve using the moment-generating function technique. Let X1, . . . , Xn be independent random variables, such that Xi ∼ N(µi, σ2) for i = 1, . . . , n. Find the distribution of Y = a1X1 + · · · + anXn.Given the moment generating function MX(t) = e 3t+8t2 , find the moment generating function of the random variable Z = 4(X − 3), and use it to determine the mean and the variance of Z.
- Find E(R) and V (R) for a random variable R whose moment-generating function ismR(t) = e2t(1-3t2)-1LetX1,X2,...,Xn be a sequence of independent and identically distributed random variables having the Exponential(λ) distribution,λ >0, fXi(x) ={λe−λx, x >0 0, otherwise (a) Show that the moment generating function mX(s) :=E(esX) =λ/(λ−s) for s< λ;LetX1,X2,...,Xn be a sequence of independent and identically distributed random variables having the Exponential(λ) distribution,λ >0, fXi(x) ={λe−λx, x >0 0, otherwise Define the random variable Y=X1+X2+···+Xn. Find E(Y),Var(Y)and the moment generating function ofY.
- Consider random variables X and Y with the joint PDF below find E[X|Y = 0] and E[Y|X = -1]Let random variables X and Y have the joint pdf fX,Y (x, y) = 4xy, 0 < x < 1, 0 < y < 1 0, otherwise Find the joint pdf of U = X^2 and V = XY.Let f(x) = ½ , -1 < x < 1 0 otherwise be a pdf of the random variable X. Find the distribution function and the pdf of Y= X2