MATH 648/STAT 930:   Probability Theory I

Fall 2019
Instructor: Zhenfu Wang

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The Course

This is a mathematically rigorous course in Probability Theory for PhD students in MATH and STATISTICS Department. The main topics include Measure theoretic foundations, laws of large numbers, large deviations, central limit theorems, Poisson processes, random walks and stopping times. We will cover the first three chapters of the textbook.

Text: Probability: Theory and Examples (Cambridge Series in Statistical and Probabilistic Mathematics) 5th Edition, by Rick Durrett.

We will use canvas to upload grades, post homework, make announcements, and share course notes. "https://canvas.upenn.edu/"

Students can discuss problems with each other or seek tips from books, articles or online rescources. But it is wrong to simply copy from any source. See Penn Office of Student Conduct.

Students with disbilities shall contact SDS directly.



Syllabus

We will cover chapter 1 - 3 in the textbook and a little bit on random walks if time permits. See Robin's explanition on how to choose a graduate Probability course (Math 546 vs Math 648-649) HERE.

A tentative detailed schedule can be found in Canvas.


Grading Policy

Your grade for the course will be determined based on the following factors:

The 1st Midterm Exam : 10%
The 2nd Midterm Exam : 10%
Homework : 80%


Exams

We will have two in-class midterms.

The 1st Midterm : Wednesday, Oct. 23.

The 2nd Midterm: Monday, Dec. 9.


Homework

Homework will be assigned weekly and due at the lecture the following Wednesday.


Important dates

Aug. 28, Wednesday, First meeting of this course.

Sept. 2, Monday, Labor Day, NO Classes.

Oct. 7, Monday, Drop Period ends.

Nov. 27, Wednesday, Friday's classes on Wednesday. No Class for this Course.

Nov. 4, Monday, Last day to withdraw from a course.

Dec. 9, Monday, Last Day of Classes.


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