Empirical methods are central to modern law practice. They are used regularly in complex business transactions, damage calculations, antitrust litigations, and discrimination litigations. Accordingly, attorneys are increasingly required to review, understand, and employ empirical data in civil and criminal litigation, appellate practice, and governmental affairs. Working with experts and developing and refuting quantitative evidence are critical skills to successful practicing lawyers. This course is designed to provide students an opportunity to bridge knowledge and practice by learning basic statistical concepts and methods for applications to litigation, legislative advocacy, and legal research. Students taking this course will gain a fundamental understanding of empirical methods and have an opportunity to learn the principals of these methods with hands-on experience using statistical software. Students will develop new skills for critical thinking and evaluation of empirical work in academic studies and expert witness reports, will gain new expertise to work with experts, and will acquire the ability to effectively develop and refute quantitative evidence.
The course will be divided into two major components. The first section of the course will introduce a broad range of topics in methodology, from study design and hypothesis testing to descriptive statistics and multivariate regression techniques in the context of legal issues faced by practicing attorneys. The second of the course will utilize this new knowledge and training to critically evaluate empirical scholarship and expert reports. No prior knowledge of mathematics, statistics, or software is required and law students from all experiential backgrounds will be able to complete the coursework and exercises based solely on class lectures and tutorials. Course grades will be based on class participation (10%), hands-on exercises (10%), a take-home midterm (30%), and a final paper (50%).
Fast Track course: Only meets for first 8 weeks of semester
|Course Number||Course Credits||Evaluation Method||Instructor||Meeting Day/Times||Room|
Research and/or analytical paper(s), 10-15 pages
|Guangya Liu, Ph.D|
|Sakai site: https://sakai.duke.edu/portal/site/LAW.553.01.F16|
|Email list: LAW.553.01.F16@sakai.duke.edu|
|Course Areas of Practice|