This course is designed to take students with a minimal background in statistics and mathematics and teach them the tools that they need to begin to test their theories and produce presentations of their results for the top journals in Political Science, International Relations, Public Policy, and other related disciplines. Students are encouraged to bring their own data sets so that they can get hands-on experiences with applying the techniques covered in this course. Thus the emphasis is on making the transitions between theory, model specification, and result presentation as seamless as possible.
The course is divided into two parts. The first part involves a thorough presentation of the logic and the central assumptions underlying the multiple ordinary least squares regression model. The second part focuses on issues that researchers typically encounter as they attempt to test their theories in a regression framework.
This is a hands-on course, meaning that a major goal is to have students learn about techniques by putting them to work with statistical software. To facilitate this, we will have lectures on each topic followed by lab sessions. In these lab sessions students will have the option of working with their own data or working with data provided by the instructor. The main statistical software program that we will use for the labs is Stata. Guides to the free program R will also be available.