7. Derive the moment-generating function M(t) for X 1(a, X). 8. Expand the moment-generating function M(t) = ex+oft®/2 in a power series in t to compute E[X3] if X ~ N(1, 2).
Let (X,,X2) be jointly distributed with the density function 2-Ax , 0 <x <x, Derive the moment generating function for (X,,X,) 13 a. b. Using the MGF in (a), derive the mean and variance of X, and X, and the correlation coefficient of (x, , x, Let (X,,X2) be jointly distributed with the density function 2-Ax , 0
Let X be a continuous random variable with values in [ 0, 1], uniform density function fX(x) ≡ 1 and moment generating function g(t) = (e t − 1)/t. Find in terms of g(t) the moment generating function for (a) −X. (b) 1 + X. (c) 3X. (d) aX + b.
Derive the moment generating function of the binomial distribution and calculate the mean and variance. p(x)=(*)*(1+p)** x = 0,1,2,...,
Derive the moment generating function of the binomial distribution and calculate the mean and variance. P(x) = x = 0,1,2,...,
Use integration to derive the moment-generating function MX (t) where fX (x) = (1/3) e^(−x/3) for x > 0. (Since we are maily interested in t near 0, assume that t < 1/3 .) Then use MX (t) to compute E(X), E(X^2), V (X), and E(X^3).
Let X be a discrete random variable. If the moment generating function of X is given by (1 -0.9+0.9e) 15. The first moment of X is Hint: Write the answer with one decimal point. Answer.
Let X be a discrete random variable. If the moment generating function of X is given by (1 – 0.6 + 0.6e')? The first moment of X is 8 Hint: Write the answer with one decimal point. Answer:
Q. 5. Let X be any random variable, with moment generating function M(S) = E[es], and assume M(s) < o for all s E R. The cumulant generating function of X is defined as A(s) = log Ele**] = log M(s), SER Show the following identities: (1) A'(0) = E[X]. (2) A”(0) = Var(X). (3) A"(0) = E[(X - E[X]))). Using the inversion theorem for MGFs, argue the following: (4) If A'(s) = 0 for all s ER, then P(X=...
12. let Mx(1) be the moment generating function of X. Show that (a) Mex+o(t) = eMx(at). (b) TX - Normal(), o?) and moment generating function of X is Mx (0) - to'p. Show that the random variable 2 - Normal(0,1) 13. IX. X X . are mutually independent normal random variables with means t o ... and variances o, o,...,0, then prove that X NOEL ?). 14. If Mx(1) be the moment generating function of X. Show that (a) log(Mx...