Homepage of MATH 180B
Introduction to Probability
Winter 2006
Department of Mathematics
University of California, San Diego
Instructor
Contact Information is posted on her homepage
Teaching
Assistant
Arthur
Berg, aberg@math.ucsd.edu
Office
Hours: Thursdays 1:30pm-3pm, AP&M 2325
Finals
Week Office Hour: Tuesday, 3pm-4pm, AP&M 2325
LECTURES
Week
1: Pitman, 5.R, 6.1, & 6.2, where
R=Review.
Week
2: Pitman, 6.3 except examples 3-5, i.e.,
no mixing of continuous and discrete for now, & 6.4 through example 3.
Week
3: Pitman, 6.5 except the very last
section on several independent normal random variable & Taylor and Karlin,
III.1 & III.2.
Week
4: Exam 1 (covers Pitman Chapter 5 Review
and Chapter 6, plus Taylor and Karlin III.1; click here for a
list of distributions/densities that you should have committed to memory);
Taylor and Karlin III.3.
Week
5: Taylor and Karlin, III.4, III.5, and
III.6.
Week
6: Taylor and Karlin, III.8, III.9, and
IV.1. Regular Matrices Maple Demo.
Week
7: Taylor and Karlin, IV.2, and IV.3.
Week
8: Exam 2 (covers Taylor and Karlin
Chapters III through IV.2). Taylor
and Karlin IV.3 and IV.4.
Week
9: Taylor and Karlin V.1, V.2, V.3
Week
10: Taylor and Karlin V.4, V.5, and V.6
Final
Exam: Will be held in Peterson
Hall Room 104
HOMEWORK
Assignment
1: Due Friday, 1/13; Pitman, 5.R.2, 5.R.5,
5.R.6, 5.R.7, 5.R.8, 5.R.10c, & 5.R.12, where R=Review.
Assignment
2: Due Friday, 1/20; Pitman, 6.1.1, 6.1.2,
6.1.3, 6.2.2, 6.2.4, & 6.2.10.
Assignment
3: Due Friday, 1/27: Pitman, 6.3.4, 6.3.5,
6.3.12, 6.4.1, 6.4.4, 6.5.2, 6.5.4, & 6.5.5.
Bonus
Problem: 6.5.3,
where the rules are that the bonus problem must be solved using only your own
brain and the Pitman book, i.e., not consulting myself, the TA, or other
resources. You may collaborate
with your classmates, in which case the points will be shared equally among the
collaborators. In order to get
credit, you or you and your collaborators must present your solution to me in
my office hours, or by appointment by Monday, January 30. Note: You may not share your ideas/work
with anyone in the course, except those identified as collaborators.
Assignment
4: Due Friday 2/3: Taylor and Karlin,
III.1 Exercise 1.3 and Problems 1.1 and 1.3 & III.2 Exercise 2.6 and
Problems 2.1 and 2.4.
Assignment
5: Due Friday 2/10: Taylor and Karlin,
III.3 Exercises 3.4 and 3.5 and Problems 3.2, 3.3, and 3.4 & III.4
Exercises 4.8 and 4.9 and Problems 4.8, 4.14, and 4.16.
Assignment
6: Due Friday 2/17:
1. Taylor and Karlin, Section III.5
Exercise 5.2, 5.5, 5.7, 5.8 and 5.9 and Problems 5.2 and 5.4 and Section III.6
Exercise 6.3 and 6.4 page 167.
2. For the Gamblerνs Ruin problem with
a total of $N and p_i=q_i=1/2, use the method of difference equations to derive
a formula for the probability of ruin starting from $1. What can you conclude about the
probability of ruin when playing an infinitely rich adversary? Using (6.7) in
III.6.1, what can be said about the expected time to ruin when playing a fair
game against an infinitely rich adversary?
3. For the Gamblerνs Ruin problem with
a total of $N, p_i=p, q_i=q, and p not equal to q, use the method of difference
equations to derive a formula for the expected length of the game when the
initial wealth of player A is $1.
What can you conclude about the expected time until ruin when playing an
infinitely rich adversary?
Assignment
7: Due Friday 2/24: Taylor and Karlin III.8 Exercises 8.2
and 8.4 and Problems 8.1, 8.2, and 8.3.
Taylor and Karlin III.9 Exercises 9.2 and 9.3 and Problems 9.2, 9.5, and
9.9. Taylor and Karlin IV.1
Exercises 1.5 and 1.10 and Problems 1.1, 1.3, 1.5, 1.6, and 1.13. Taylor and Karlin IV.2 Exercise 2.6 and
Problems 2.1 and 2.4.
Bonus
Problem: Show that the generating function of
the offspring distribution has two fixed points in [0,1] if and only if the
derivative is greater than 1 at 1, where the rules are the same as in
assignment 3. Due by Monday 2/27.
Assignment
8: Due Friday 3/10:
1. Modify Taylor and Karlin IV.3
Exercise 3.1 by adding two states 8 and 9 and the making following changes to
the transition matrix: P_{0i}=1/2 for i=1, 8, P_{89}=1, and P_{90}=1. Find an integer N such that n>=N
implies P_{ii}^{(n)}>0 for all i.
2. Taylor and Karlin IV.3 Exercise 3.3
and Problems 3.2 and 3.3.
3. Consider an irreducible and positive
recurrent Markov chain. Let r_i be
the expected number of visits to i after time 0 that occur at or before the
first return to 0 starting from state 0.
Show that
1. r_0=1
2. r_i=sum_j r_jp_{ji} for all i.
3. r_i is positive and finite for all
i.
4. Taylor and Karlin IV.4. Exercise 4.3
and Problems 4.7 and 4.8.
Assignment
9: Due Friday 3/17:
1. Taylor and Karlin V.1 Exercises 1.3,
1.6, and 1.7 and Problems 1.1 and 1.9.
2. Taylor and Karlin V.2 Exercises 2.3
and 2.4 and Problems 2.1, 2.4, and 2.7.
3. Taylor and Karlin V.3 Exercises 3.6
and 3.7 and Problems 3.1-3.4, 3.6 and 3.7. I basically did 7 in class, but note that
P(W_{k+1}<=t)=P(N((0,1])>=k+1).
In class I had a k rather than a k+1, so be sure the check the
inequalities for correctness.
Recommended
1. Pitman 4.2.5, 4.2.6, 4.2.15, 4.2.16.
(Doing these will reinforce the characterization of a Poisson process in terms
of independent exponential lambda sojourn times. Note that what T&K label as W, P labels as T, and what
T&K label S, P labels as W.)
2. Problems from Taylor and Karlin V.4
Exercises 4.4 and 4.5 and Problems 4.6, 4.8, 4.9, and 4.10.