Introduction to Statistical Theory & Methodology-3 (420-3-20)

Instructors

Wenxin Jiang
847.491.5081
2006 Sheridan, Room 203/Department of Statistics

Meeting Info

University Hall 122: Tues, Thurs 12:30PM - 1:50PM

Overview of class

The goal of this Stat 420-1,2,3 sequence is to provide a comprehensive introduction to statistical theory and methodology at a level not requiring advanced probability theory (i.e. measure theory). The course sequence will cover all major areas of statistical theory including distribution theory, theory of estimation and hypothesis testing, large-sample theory, Bayesian methods, and decision theory. The emphasis of Stat 420-3 will be on those theoretical topics that are used in the development of statistical methods. Application of theoretical ideas to models used in practice, such as the normal-theory linear model and its various extensions, will be considered in detail. The course is intended to be useful to students in areas such as engineering and economics as well as students in statistics.The third quarter surveys more advanced topics and the emphasis may differ each year. This year Stat 420-3 will have three parts: Part A on selected topics in Bayesian statistics, including large sample methods, hypothesis testing, and model selection in the Bayesian way; Part B on selected topics in econometric methods, useful for handling non-standard linear regression with heteroscedasticity and correlated errors; Part C on student presentations, to study modern development of statistics based on recent journal articles that are related to basic concepts learned in the whole sequence of this course.

Registration Requirements

Probability Theory (e.g., Math 330), calculus (e.g.,Math 215), linear algebra (e.g., Math 217) and Statistics 420-1, 420-2.

Learning Objectives

Some theory and methodology in Bayesian statistics and in econometrics.

Teaching Method

Lectures and student presentations

Evaluation Method

Grades will be based on homework, exam and presentation of a related paper.

Class Materials (Required)

None is required.

Class Materials (Suggested)

READINGS: Ghosh, J.K., Delampady, M., Samanta, T., (2006). An Introduction to Bayesian Analysis: Theory and Methods, Springer.

Hansen, B., "Econometrics", (2022), Princeton University Press.

Enrollment Requirements

Enrollment Requirements: REASON: Pre-registration is not allowed for this class. Please try again during regular registration.
Add Consent: Department Consent Required