Meeting times and location
2:00 pm - 3:00 pm, Cupples I 115
Web page: http://www.math.wustl.edu/~russw/math494/
Introduction
Math 494 covers the mathematical theory of statistics, including the theory of estimation, minimum variance and unbiased estimators, maximum likelihood theory, Bayesian estimation, prior and posterior distributions, confidence intervals for general estimators, standard estimators and distributions such as the Student-t and F-distribution from a more advanced viewpoint, hypothesis testing, the Neymann-Pearson Lemma (about best possible tests), linear models, and other topics as time permits.
Prerequisites
The prerequisite is Math 493, or equivalent mathematical maturity and experience.
My contact info:
| Russ Woodroofe |
| Cupples I 114 |
| Office hours: Tuesday 2 - 5pm + by appt |
| russw at math,wustl,edu |
Textbook
Robert Hogg, Allen Craig, and Joseph McKean, Introduction to Mathematical Statistics, 6th edition.
We will cover selected topics from Chapters 3-9, including most of Chapter 6. If there is time, we may discuss some material from Chapter 10. I will update the schedule periodically with a record of the topics covered.
If you need to refer to facts from probability, the textbook from last semester is still available online. (Chapters 1, 2, and part of 3 of the current text also contain a terse overview of the topics from last semester.)
Grading
Your grade will be based on 2 take-home midterm exams and one sit-down final exam, together with weekly homeworks and possibly an occasional quiz, in the proportions
| Midterm exams | 20% each |
| Final exam | 30% |
| Homework and quizzes | 30% |
The take-home midterms will be due February 23 and April 6.
The final is scheduled by the University for May 9, 6 - 8pm.
If you are taking the course Pass/Fail, you need to do the equivalent of C- work to pass.