Prof: | Robert L. Wolpert | wolpert@stat.duke.edu | OH: Mon 4:30-5:30pm, 211c Old Chem | ||
TAs: | Jonathan Christensen | jonathan.christensen@stat.duke.edu | OH: Tue 4:00-6:00pm, 211a Old Chem | ||
Class: | Mon/Wed 1:25p-2:40p, 127 Soc Psy | ||||
Text: | Sidney Resnick, | A Probability Path | Additional references | ||
Opt'l: | Patrick Billingsley, | Probability and Measure (3/e) | (a classic) | ||
Jacod & Protter, | Probability Essentials (2/e) | (easier than Resnick, $40) | |||
Rick Durrett, | Probability Theory & Examples (4/e) | (more complete) |
Week | Topic | Homework | |
---|---|---|---|
I. Foundations of Probability | Problems | Due | |
Aug 25-27 | Probability spaces: Sets, Events, and σ-Fields | hw1 | Sep 03 |
Sep 01-03 | Construction & extension of Measures | hw2 | Sep 10 |
Sep 08-10 | Random variables and their Distributions | hw3 | Sep 17 |
Sep 15-17 | Expectation & the Lebesgue Theorems | hw4 | Sep 24 |
Sep 22-24 | Inequalities, Independence, & Zero-one Laws | hw5 | Oct 01 |
Sep 29-01 | Review & in-class Midterm Exam I ('12, '13) | Hists: | Exam, Course |
II. Convergence of Random Variables and Distributions | |||
Oct 06-08 | Convergence: a.s., pr., Lp, Loo. UI. | hw6 | Oct 22 |
--- Fall Break (Oct 11-14) --- | |||
Oct -15 | Expectation Inequalities | ||
Oct 20-22 | Strong & Weak Laws of Large Numbers | hw7 | Oct 29 |
Oct 27-29 | Fourier Theory and the Central Limit Theorem | hw8 | Nov 05 |
III. Conditional Probability & Conditional Expectations | |||
Nov 03-05 | Cond'l Expectations & the Radon-Nikodym thm | hw9 | Nov 10 |
Nov 10-12 | Review & in-class Midterm Exam II ('12, '13) | Hists: | Exam, Course |
Nov 17-19 | Introduction to Martingales (a, b) | hw10 | Nov 24 |
Nov 24 | Heavy tails and Extreme Values | ||
--- Thanksgiving Break (Nov 26-30) --- | |||
Dec 08 | Review for Final Exam, Mon 1:25-2:40 | ||
Dec 14 | 2-5pm Sun: In-class Final Exam ('12, '13) | Hists: exam, course |
Students are expected to be well-versed in real analysis at the level of W. Rudin's Principles of Mathematical Analysis or M. Reed's Fundamental Ideas of Analysis— the topology of Rn, convergence in metric spaces (especially uniform convergence of functions on Rn), infinite series, countable and uncountable sets, compactness and convexity, and so forth. Try to answer the questions on this analysis diagnostic quiz to see if you're prepared. Most students who majored in mathematics as undergraduates will be familiar with this material, but students with less background in math should consider taking Duke's Math 531, Basic Analysis I: F09 vsn (somewhat more advanced than Math 431, Advanced Calculus I, but that's a good second choice) before taking this course. It is also possible to learn the background material by working through one of the standard texts (like the two listed above) and doing most of the problems, preferably in collaboration with a couple of other students and with a faculty member (maybe me) to help out now and then. More advanced mathematical topics from real analysis, including parts of measure theory, Fourier and functional analysis, are introduced as needed to support a deep understanding of probability and its applications. Topics of later interest in statistics (e.g., regular conditional density functions) are given special attention, while those of lesser statistical interest may be omitted.
Most students in the class will be familiar with undergraduate-level probability at the level of STA 230. While this isn't required, students should be or become familiar with the usual commonly occurring probability distributions (here is a list of many of them).
Some weeks will have lecture notes added (click on the "Week" column if it's blue or green). This is syllabus is tentative, last revised , and will almost surely be superseded— reload your browser for the current version.
Homework problems are awarded zero to three points each, based on your success in communicating a correct solution. For the full three points the solution must be clear, concise, and correct; even a correct solution will lose points or be returned ungraded if it is not clear and concise. Neatness counts. Consider using LaTeX and submitting your work in pdf form if necessary (it's good practice anyway). Homeworks may be submitted in paper form (just bring them to class on Wednesday) or electronically in the form of pdf files (submit as Sakai "Assignments" or send by e-mail to the course TA, jonathan.christensen@stat.duke.edu).
In-class Midterm and Final examinations are closed-book and closed-notes with one 8½"×11" sheet of your own notes permitted. Tests from recent STA711 offerings are available to help you know what to expect and to help you prepare for this year's tests:
Fall 2012: | 1st Midterm | 2nd Midterm | Final Exam | ||||
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Fall 2013: | 1st Midterm | 2nd Midterm | Final Exam |
You may discuss and collaborate in solving homework problems, but you may not copy— each student should write up his or her solution. Cheating on exams, copying or plagiarizing homeworks or projects, lying about an illness or absence and other forms of academic dishonesty are a breach of trust with classmates and faculty, and will not be tolerated. They also violate Duke's Community Standard and will be referred to the Graduate School Judicial Board or the Dean of the Graduate School.