Through the legal residency class, students reflect upon, and internalize, the legal and professional skills developed through their legal residencies. Students: establish learning goals for the semester; apply attorney-client confidentiality and privilege concepts; submit weekly time sheets; write regular reflections regarding their experiences; participate in discussion forums and workshops on professionalism topics; engage in self-evaluation; and complete a final reflective project.

This introductory course instructs on the key laws, regulations and policies that govern sports betting and gaming in the United States. To that end, students learn insights on the most influential developments - including significant sports betting controversies, critical legislative efforts and instrumental court decisions - in this burgeoning area of law. Specific topics include: the rise and fall of the Professional and Amateur Sports Protection Act (PASPA); applications of the federal Wire Act and the Unlawful Internet Gambling Enforcement Act; the interplay between tribal compacts and sports wagering; variations of states' gaming laws; intellectual property and privacy issues stemming from real-time data in sports betting; the legality of fantasy sports and daily fantasy sports; strategic guidance on possible regulatory controversies in a post-PASPA world; and other topics of importance to industry actors. Eligibility: Open to all except 1Ls. This course may be taken for an S/U grade.

Effective management of human activities in ocean, coastal and Great Lakes areas is critical to our future. This course provides a foundation for students from various backgrounds to understand US marine policy and how it relates to their future careers in research, policy, law, or management. While focused on US marine policy, the course also provides international context, including the UN Law of the Sea and other related conventions on pollution, fisheries, and resource protection.

An introduction to multivariate statistical methods, including principal components, discriminant analysis, cluster analysis, factor analysis, multidimensional scaling, and MANOVA. Additional topics include generalized linear models, general additive models, depending on the interests of class participants. This course completes a solid grounding in modern applications of statistics used in most research applications. The use of statistical software, such as JMP, S PLUS, or R, is fully integrated into the course.