Fall Semester: M384C / SSC384 Topic 2 / CSE 384R
Graduate Course Description
Course Title: 
Mathematical Statistics I 
Course Number(s): 

Time of Lecture: 
TTh 5:006:30 pm 
Instructor: 
Prof. Mary Parker 
Brief description:
The two semesters of this course (SSC384 Topic 2 and SSC384 Topic 3) are designed to provide a solid theoretical foundation in mathematical statistics.
During the TWOSEMESTER course, the statistical topics include the properties of a random sample, principles of data reduction (sufficiency principle, likelihood principle, and the invariance principle), and theoretical results relevant to point estimation, interval estimation and hypothesis testing.
During the first semester, SSC 384 Topic 2, students are expected to use their knowledge of an undergraduate upperlevel probability course and extend those ideas in enough depth to support the theory of statistics, including some work in hierarchical models to support working with Bayesian statistics in the second semester. Students are expected to be able to apply basic statistical techniques of estimation and hypothesis testing and also to derive some of those techniques using methods typically covered in an undergraduate upperlevel mathematical statistics course. A brief review of some of those topics is included. Probability methods are used to derive the usual sampling distributions (min, max, the t and F distributions, the Central Limit Theorem, etc.) Methods of data reduction are also discussed, particularly through sufficient statistics. This includes the five chapters of the text and part of the sixth chapter as well as some additional material on estimation and hypothesis testing.
Prerequisite:
M362K, Probability, and M378K, Introduction to Mathematical Statistics, or the
equivalent. Course descriptions of 362K
and 378K are
available on the web and more information about equivalencies is available from
http://www.ma.utexas.edu/users/parker/384/prereq/
Textbook: Statistical Inference by George Casella and Roger L. Berger, second edition
Consent of Instructor Required: Yes.
Prof. M. Parker 
RLM 13.160 

Email: parker@math.utexas.edu 
Homepage: http://www.ma.utexas.edu/users/parker/ 
Last updated August 20, 2013 . Mary Parker