Math 5062: Theory of Statistics II

Instructor: Likai Chen (likai.chen[at]wustl.edu)

Lectures: 2:00-2:50 p.m on M/W/F in Mallinckrodt 302

Office hour:

Schedule

Topics covered

This course is the second course in the sequence of mathematical statistics for the Ph.D. qualifying exam. For the first half semester, we will cover asymptotic theory, including convergence in measure/distribution, LLN, CLT, limit theorems, integral and density approximations; for the second half semester, we shall consider several paradigms for testing, such as the Neyman-Pearson, likelihood ratio, neo-Fisherian, Bayesian approaches. Modern topics will be introduced as time permits. This course is theorem-proof based, applications will not be emphasized, and examples will be theoretical. Statistical software is not part of the course.

Prerequisites

Math 5061 (Theory in Statistics I) or the equivalent, or permission of instructor.

Textbook

Krishna B. Athreya and Soumendra N.Lahiri
Measure Theory and Probability Theory
Thanks Soumendra N.Lahiri and Todd Kuffner for sharing Electronic Access Errata

Exams

There will be one midterm and one final. All exams are closed book and closed note. No web-enabled devices may be used. One page (letter size and two-sided) note may be brought to exams. Calculators are allowed but not required.

Make-up exams are strongly discouraged. If you are aware of a conflict, please inform the instructor at least one week before the exam.

Homeworks

There will be hws about every two weeks throughout the semester. Homework is due on Thursday midnight. NO LATE HOMEWORK WILL BE ACCEPTED.

Grades

Your grade will be based on homeworks, midterm and final exam.

Midterms 35%
Final 35%
Homework 30%

The threshold for each grade

A A- B+ B B- C + C C -
90 or above88-90 86-88 80-86 78-90 75-78 65-75 60-65
Only very few top student may get A+.