Prerequisite: None

Exam Type: No Exam

Tools and concepts of empirical methods and data analysis are increasingly used in litigation, regulation, legal policymaking, and research. This course aims at providing students with basic training in using such tools and concepts. No prior work in empirical methods or statistics will be required or assumed.

The course is hands-on and applied in nature and taking it will count toward the J.D. Experiential Learning requirement. Students will be taught how to program in R, which is a statistical/empirical software package, and subsequently use it to analyze data in home exercises and a final project. The course is designed to provide students with the ability to subsequently carry out an empirical analysis in their practice or research.

Topics covered will include descriptive statistics and graphs, probability, statistical inferences and hypothesis testing, correlation, simple and multiple regressions, dummy variables, panel data, and distinguishing between correlation and causation. In carrying out exercises and their final project, students will use actual datasets regarding law-related settings that will be provided to them.  

There will be no exam. Instead, students will be required to complete and submit (ungraded) problem sets, as well as to carry out a final project. The grade of the course will primarily be based on this final project.

Note: The course will meet for eighteen, two-hour sessions, which will all take place during the time slot assigned to the course and will be concentrated in the first two months of the semester.