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Fall 2023 Course

Empirical Methods and Data Analysis for Lawyers

Prerequisites: None

Exam Type: No Exam

Empirical data, as well as empirical tools and concepts, are increasingly used in litigation, regulation, and legal policymaking and research. This course aims at providing students with basic training in using statistical and empirical tools. No prior work in empirical methods or statistics will be required or assumed.
The course is hands-on and applied in nature, and the course will therefore count toward fulfilling the law school’s experiential learning requirement. Students will learn to use a standard statistical/empirical software package and subsequently use it to analyze data.

Topics that will be covered include descriptive statistics and graphs, statistical inferences and hypothesis testing, correlation, regressions (both simple regression and multiple regression), and distinguishing between correlation and causation. Students will use actual data, and law-related examples will be used to illustrate the concepts and tools taught.

There will be no exam. Instead, students will be required to submit ungraded exercises and to submit an empirical analysis of a dataset. Grading will be based on the student’s empirical analysis of the dataset.

Note: The course will meet for 18 two-hour sessions, which will all meet during the time slot of the course and will be concentrated during the first two months of the semester.