Statistical Inference in Law (7512): Drawing inferences from quantitative data lies at the heart of many legal and policy decisions. This course provides the tools, concepts, and framework for lawyers to become sophisticated consumers of quantitative evidence and social science. The course will begin with an overview of basic statistical concepts that will bring everyone to the point where they can read and evaluate empirical studies. We will then focus on a number of empirical debates -- for example, does the death penalty deter murder, do concealed handgun laws influence crime -- as a springboard to teach the logic and terminology of statistical/econometric evaluation of law and policy (regression, statistical significance, identification). No background, beyond high school algebra, is assumed. Anyone who 1) will work in litigation (whether corporate, securities, antitrust, employment discrimination, environmental law) or in public policy, 2) wants to be a better citizen or 3) wants to understand the challenges of establishing causal relationships, and who doesn't already have a strong understanding of statistics will find this course useful. Elements Used in Grading: Attendance, written and oral assignments, response papers, and a final project. To avoid math phobias and fears about ringers from the econ or stats departments, the course is graded as a mandatory pass-fail course.

Statistical Inference in Law (7512): Drawing inferences from quantitative data lies at the heart of many legal and policy decisions. This course provides the tools, concepts, and framework for lawyers to become sophisticated consumers of quantitative evidence and social science. The course will begin with an overview of basic statistical concepts that will bring everyone to the point where they can read and evaluate empirical studies. We will then focus on a number of empirical debates -- for example, does the death penalty deter murder, do concealed handgun laws influence crime -- as a springboard to teach the logic and terminology of statistical/econometric evaluation of law and policy (regression, statistical significance, identification). No background, beyond high school algebra, is assumed. Anyone who 1) will work in litigation (whether corporate, securities, antitrust, employment discrimination, environmental law) or in public policy, 2) wants to be a better citizen or 3) wants to understand the challenges of establishing causal relationships, and who doesn't already have a strong understanding of statistics will find this course useful. Elements Used in Grading: Attendance, written and oral assignments, response papers, and a final project. To avoid math phobias and fears about ringers from the econ or stats departments, the course is graded as a mandatory pass-fail course.