ORF 526: Probability Theory, Fall 2017


Basic info

Course description: This is a graduate introduction to probability theory with a focus on stochastic processes.
Topics include: an introduction to mathematical probability theory, law of large numbers, central limit theorem, conditioning, filtrations and stopping times, Markov processes and martingales in discrete and continuous time, Poisson processes, and Brownian motion.

The course is designed for PhD students whose ultimate research will involve rigorous mathematical probability. It is a core course for first year PhD students in ORFE and it is also taken by students in several other areas, such as Applied & Computational Mathematics, Computer Science, Economics, Electrical Engineering, and more.

Prerequisites: Undergraduate level probability theory.

Instructor: Miklos Z. Racz
Lecture time and location: TuTh 3:00 - 4:20 pm, 008 Friend Center
Office hours: W 9:00 - 11:00 am, 204 Sherrerd Hall

Teaching Assistant (AI): Zongjun Tan
Office hours: F 10:00 am - 12:00 pm, 107 Sherrerd Hall (Library room)



Grading and course policies

Grading: There will be homework problem sets throughout the semester (approximately weekly), as well as a midterm and a final exam.
Your final score is a combination of your performance in these, with the following breakdown:
Midterm info: Thursday, October 26, in class

Final info: TBD

Homework and collaboration policy:
Please be considerate of the grader and write solutions neatly. Unreadable solutions will not be graded.
Please write your name, Princeton email, and the names of other students you discussed with on the first page of your HW.
No late homework will be accepted. Your lowest homework score will be dropped.

You should first attempt to solve homework problems on your own.
You are encouraged to discuss any remaining difficulties in study groups of two to four people.
However, you must write up the solutions on your own and you must never read or copy the solutions of other students.
Similarly, you may use books or online resources to help solve homework problems, but you must always credit all such sources in your writeup, and you must never copy material verbatim.

Advice: do the homeworks! While homework is not a major part of the grade, the best way to understand the material is to solve many problems. In particular, the homeworks are designed to help you learn the material along the way.

Email policy: For questions about the material, please come to office hours.
For general interest questions, please post to the course Piazza page.
This facilitates quick and efficient communication with the class.
Please use email only for emergencies and administrative or personal matters.
Please include "ORF 526" in the subject line of any email about the course.



Resources

Main resource (required text): Additional resources: There are many other texts that cover first year graduate probability. While the focus and scope of this course is slightly different, these texts can be valuable resources. David Aldous has an extensive annotated list here and here; in particular, consider consulting:
Piazza: The course has a Piazza page.
Think of this as a Q&A wiki for the course, use it for questions and discussions.



Schedule

Classes begin on Thursday, September 14.


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