統計學程A類(統計理論)課程三選一必修。

This is an advanced level course which emphasizes the laws of probability needed for making proper inference from data. During this semester, we will focus on the parts of probability theory that are essential to understanding statistics, i.e., the distribution theory of random variables–both exact and large sample theory. In addition, this course is also the starting place for you to learn more about statistical inferences as well as some methodologies of simulation, such as the method of Monte Carlo, and bootstrapping. These theories and methods are heavily used in economics, finance, and management science. It is critical that students (you) work the problems. Most (all?) problems can be worked using several methods which can help you discover how many ways you can work each exercise! I will assign a selection of problems each week; try as many as you can. If time permits, I will identify some additional problems that you may want to work to prepare for entrance examinations into some master programs.

The pace of this course is fairly rapid. There are about 300 pages of text that we will cover; therefore, if you are having difficulty keeping up or simply have questions that we do not get to in class, please come and see me–in addition to my office hours, I am usually in my office throughout the day. The lectures will cover the key and/or subtle points of the course material (at least as I see them!). I will assume that you are reading the book; therefore, I will not attempt to cover every detail of every section. However, you are responsible for the text material in addition to the lectures. I am always happy to answer questions about this material, but depending on the question, I may want to talk with you outside of lecture.

Hogg, R.V., J.W. McKean, and A.T. Craig (2005) Introduction to Mathematical Statistics, Sixth Edition, Pearson Education, Inc., ISBN 0-13-122605-3