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Final

STAT3100 Final: 3100_F14_Sample_Final_Number2

2 Pages
75 Views
Fall 2014

Department
Statistics
Course Code
STAT 3100
Professor
Jeremy Balka
Study Guide
Final

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STAT*3100 F14
A few more practice questions for the final exam
For the final exam you are responsible for all the material we have covered in the course. This document
contains some practice questions on the later material (after the midterm).
1. Suppose XExp(1). Derive the distribution of Y=eX2using:
(a) The transformation (change of variable) technique.
(b) The distribution function technique.
2. Suppose XUnif(1,3). What is the distribution of Y=|X|?
3. Suppose the random variable Xhas the probability density function:
f(x;α, β) =
α
βαxα1e(x/β)αfor x > 0
0elsewhere
where α > 0, β > 0. What is the distribution of Y= (X/β)α?
4. Show that if Xhas a geometric distribution, P(X=b+c|X > b) = P(X=c).
5. In class and the notes we defined a geometric random variable (X, say) to be the number of
trials required to get the first success in repeated independent Bernoulli trials. We learned that
E(X) = 1
p,V ar(X) = 1p
p2, and MX(t) = pet
1(1p)et(for t < ln(1 p)).
Many sources define a geometric random variable (Y, say) to be the number of failures before
getting the first success. Suppose we want to work with this alternative definition.
(a) What is the relationship between Xand Y?
(b) What is the probability mass function for the random variable Y?
(c) What is the support of this probability mass function?
(d) What is the mean of Y?
(e) What is the variance of Y?
(f) What is the moment generating function of Y?
6. Hanhart syndrome is a rare genetic disorder that affects approximately one in 15,000 live births in
North America. Individuals with Hanhart syndrome can have a number of physical deformities,
including malformed fingers, toes, and limbs. Suppose 10,000 North American live births are
randomly sampled.
(a) Using the binomial distribution, what is the probability that at least one individual has
Hanhart syndrome?
(b) Using the Poisson approximation to the binomial distribution, what is the probability that
at least one individual has Hanhart syndrome?
7. Give the probability mass function for the random variable in the following situations, including
the value(s) of the parameter(s) and the support of the function.
(a) The number of hearts if 10 cards are dealt without replacement from a standard deck.
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Description
STAT*3100 F14 A few more practice questions for the nal exam For the nal exam you are responsible for all the material we have covered in the course. This document contains some practice questions on the later material (after the midterm). 1. Suppose X Exp(1). Derive the distribution of Y = eusing: (a) The transformation (change of variable) technique. (b) The distribution function technique. 2. Suppose X Unif(1;3). What is the distribution of Y = jXj? 3. Suppose the random variable X has the probability density function: 8 > x1e(x=) for x > 0 < f(x;;) = > 0 elsewhere : where > 0; > 0. What is the distribution of Y = (X=) ? 4. Show that if X has a geometric distribution, P(X = b + cjX > b) = P(X = c). 5. In class and the notes we dened a geometric random variable (X, say) to be the number of trials required to get the rst success in repeated independent Bernoulli trials. We learned that 1 1 p pe E(X) = p , V ar(X) = p2 , and MX(t) = 1(1p)e(for t < ln(1 p)). Many
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