1. Derive the mean and variance for a discrete distribution based on its moment generating function MX(t) = e 8 t 2 , t ∈ (−∞,∞).

As you given the question mean is zero and variance 16.
But the question given/Written is not proper way.mention the question proper way.
1. Derive the mean and variance for a discrete distribution based on its moment generating function...
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,...,
Problem 1 Let Xi, ,Xn be a random sample from a Normal distribution with mean μ and variance 1.e Answer the following questions for 8 points total (a) Derive the moment generating function of the distribution. (1 point). Hint: use the fact that PDF of a density always integrates to 1. (b) Show that the mean of the distribution is u (proof needed). (1 point) (c) Using random sample X1, ,Xn to derive the maximum likelihood estimator of μ (2...
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).
2. Consider the Poisson distribution, which has a pdf defined as: a) Derive the moment generating function. b) Use the moment generating function and the method of moments to find the mean and the variance. c) If X follows the Poisson distribution with Xx - 2.3, and Y follows a Poisson distribution with XY-54, what is the distribution of the sum X + Y, assuming that X and Y are independent?
Derive the expectation and variance of lognormal distribution WITHOUT using the moment generating functions.
Let X U(0,theta). Find the moment generating function of X and show how to use it to find the mean and variance of X.I think this follows the uniform distribution so..mean = (theta1 + theta2)/2variance = [(theta2- theta1)^2]/ 12moment generating function = [e^(t*theta2) - e^(t*theta1)]/(t * (theta2-theta1))I think the beginnning of the problem means that theta1 is 0? I'm not sure how to show the moment generating function.
Problem 2 Suppose a distribution has the following moment generating function: MC (1-2)/a Find the mean and variance.
Use the given moment-generating function, Mx(t), to identify the distribution of the random variable, X in each of the following cases. (Specify the exact type of distribution and the value(s) of any relevant parameters(s): 1. (a) M(-3 (b) M() exp(2e -2) Ce) M T112t)3 (f) Mx(t) = ( 1-3t 10 ) (d) Mx(t)= exp(2t2_t) (e) Mx(t)= - m01 -2t)!
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).