Teaching

Current Courses: Spring 2018

AMATH 490: Statistics and the Law

Instructors:

Meeting Time:

Fridays 2:30 - 4:30, Lewis Hall 208.

Course Description and Objectives

There is a natural tension between legal and statistical thinking. Legal proceedings aim to answer binary questions of causation; statistical tools aim to quantify uncertainty and establish correlations. Yet the role of statistics in the law has been growing, and concepts ranging from basic notions of probability to complex regression and epidemiological models are routinely presented to judges and juries as a part of legal proceedings. Our goal is to explore the role of statistics in the judicial process, outline fundamental aspects of the legal system and its use of statistical methodology, and provide numerical examples based on data to illustrate uses of statistics in law.

We draw on many examples and ideas from the well-known book Statistics for Lawyers by Finkelstein and Levin.
We focus on fundamental tensions of statistical methodology in the context of the legal system to show examples of usage as well as the limitations and fundamental philosophical differences between existing methods and the legal questions they are intended to answer. In addition to the textbook, we will read and discuss several articles. Participation in the course will also include hands-on analyses in R using real data.

The course covers three interconnected components:

• Overview of the legal system, the ways the courts handle questions informed by statistics, and examples of such questions.
• Statistical methods as they arise in the legal system, including statistical significance, odds ratios, linear and logistic regression, epidemiological models, and other examples.
• Future directions: more effective approaches to answering legal questions using advanced data science techniques.

Prerequisites

Basic probability and statistics (Math/Stat 394 & 395 or Stat 390) or equivalent are required, and familiarity with the R programming language and with linear algebra is strongly encouraged. Petitions for exceptional cases will be considered.

Grading Policy

Grading will be based on class participation, homework assignments, and a final project.