
Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community for help and clear up your study doubts
Discover the best universities in your country according to Docsity users
Free resources
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
Material Type: Exam; Professor: Zheng; Class: Statistical Theory I; Subject: Mathematics (MTH); University: Missouri State University; Term: Fall 2009;
Typology: Exams
1 / 1
This page cannot be seen from the preview
Don't miss anything!
Math 540/640: Statistical Theory I
Instructor: Songfeng (Andy) Zheng
Note: Please write your work on a piece of paper clearly. Please show your work in detail.
Problem 1: The number of defective components produced by a certain process follows a Poisson distribution with mean k. Each defective component has probability p 0 as being repairable.
a. Find the probability that exactly N defective components are found.
b. Suppose we have exactly N defective components, let Y be the number of repairable components, find the probability distribution of Y.
c. Find the moment generating function of the distribution you obtained in part b.
d. What is the probability that we find exactly N defective components, and among them, n are repairable?
Problem 2: A continuous random variable X has probability density function f (x) as
f (x) =
{ ce−βx, if x > 0 0 , otherwise
where β > 0 is a known constant, and c is an unknown constant.
a. Please find c.
b. Please find the cumulative distribution function.
c. Using the result from b, please find P (X > a + b|X > a), where a > 0 and b > 0 are known constants.
d. Find the moment generating function of X, please also specify the range of t in the moment generating function.
e. Using the result in d, find E(X).
Problem 3: Let N be a discrete random variable with all the possible values { 2 , 3 , · · ·}. Let function p(n) be
p(n) =
Cα nα^ log n
, if n = 2, 3 , · · ·
and p(n) = 0 otherwise; where Cα > 0 is a constant depending on α. For what values of α, p(n) is a probability distribution? For what values of α, the expected value E(N ) exists? Please prove your conjecture. [You don’t need to evaluate Cα or E(N ).]