Problem 4 (10 Points) Derive the moment generating function and the characteristic function for a geometric...
The geometric random variable X has moment generating function given by EetX) = p(1 – qe*)-7, where q = 1- p and 0 < p < 1. Use this to derive the mean and variance of X.
(10 points) 4. The moment generating function of a random variable Y is , for t e R, where k is a constant. (a) Find the mean of Y. (b) Determine Pr(Y <1Y <2) (c) Find th e cumulative distribution function of Y, with domain R.
(10 points) 4. The moment generating function of a random variable Y is , for t e R, where k is a constant. (a) Find the mean of Y. (b) Determine Pr(Y
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc useful property of moment generating functions is that they make it relatively casy to compute weighted sums of independent random variables: Z=aX+BY M26) - Mx(at)My (Bt). (A) Derive the MGF for a Poisson random variable X with parameter 1. (B) Let X be a Poisson random variable with parameter 1, as above, and let y be a Poisson random variable with parameter y. X...
problem 3 and 4 please.
3. Find the moment generating function of the continuous random variable & such that i f(x) = { 2 sinx, Ox CT, no otherwise. 4. Let X and Y be independent random variables where X is exponentially distributed with parameter value and Y is uniformly distributed over the interval from 0 to 2. Find the PDF of X+Y.
Problem 6. Suppose the moment generating function of a random variable, X, is Compute the third moment of Y, where Y-1+2X
5 (10 points) X and Y are independent random variables with common moment generating function M(t) eT. Let W X + Y and Z X - Y. Determine the joint moment generating function, M(ti, t2) of W and Z Find the moment generating function of W and Z, respectively
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).
MoM stands for Method of Moments.
4. (a) If X Geometric(p), prove that the moment-generating function for X is Mx(t) pe 1-(1-p)e' (b) Use your result of part (a) to show that E(X) = p and V(X) = Now, we have X1, X2,... X, d Geometricíp). (c) Find a MoM estimator for p based on the first moment. (d) Explain why your estimator makes sense intuitively. (e) Use the following data to give a point estimate of p: XnGeometric(p 3,...
(6) (15 points) The moment generating function for a normal random variable N (17,0?) is given by M(t) =e(+rt). Given Y with pdf N (4,0%), show that, if X and Y are independent, then the random variable 2 = x + Y is normally distributed with variance o + oz and mean 41 + 12. Please state clearly which properties of the moment generating function you are using.
10. The moment generating function of the random variable X is given by My(t) = exp{2e* – 2} and that of Y by My(t) = fet +. Assuming that X and Y are independent, find (a) P{X + Y = 2). (b) P{XY = 0}. (c) E(XY).