In this course, I will give a graduate level of introduction to regression models, which are commonly used in policy research, political science, and many other social science fields. This course focuses on linear regression models with interval variables (mostly cross-sectional analysis). The course starts with descriptive statistics. We will learn the basic properties of estimators, hypothesis testing, and the uses of many varieties of independent variables. We will also discuss the casual modeling as a way of understanding the inter-relationships among variables and of understanding why regression coefficients change. Then, the course will cover statistical inference, discussing the assumptions behind the classical linear regression models. Finally, we discuss the implications of a variety of violations of the classical assumptions. The course will also cover some basic concept of time-series model and limited variable models.

The course consists of lectures, discussions, exams, and homework assignments. We all know that the best policy to learn statistics is by doing it. Hence, there will be computer assignments to give you practical experience with using STATA and applying the statistical techniques. There will be one article summaries/critiques and one manuscript review assignment, intended to prepare you for a typical task by academics.