This course will examine the precepts of trademark and unfair competition law. We will investigate issues of ownership, registration, goodwill, misappropriation, infringement, and dilution in the context of words, phrases, symbols, slogans, product design, and trade dress. The course will also explore related issues such as false and comparative advertising, rights of publicity, and fair use. Hybrid Juris Doctor students cannot take this course for an S/U grade.

Appellate Advocacy is a writing intensive course designed to teach the different components of appellate brief writing, as well as effective appellate oral advocacy. One or two case problems (depending upon the particular professor) are assigned throughout the semester, modeled after actual court cases. Students will be taught how to master the facts of a case, the rule of law applicable to the particular legal problem, and the policy underpinning the rule of law. Paramount goals of the course include professionalism and instructing students on clear, persuasive, organized, and strategic written and oral communication skills necessary for effective legal advocacy. While AA focuses on the appellate practice setting, the written and oral advocacy skills students will acquire are applicable to all settings of legal practice. Grading will be based on one or two appellate briefs, oral arguments, meaningful class participation and other assignments. This course cannot be taken for an S/U grade.

Functions, sets and their use in mathematical models in business, economics and finance, including probability, linear systems and mathematics of finance; basic concepts of differential calculus and relevant applications.

Course in design of experiments with applications to quality improvement in industrial manufacturing, engineering research and development, or research in physical and biological sciences. Experimental factor identification, statistical analysis and modeling of experimental results, randomization and blocking, full factorial designs, random and mixed effects models, replication and sub-sampling strategies, fractional factorial designs, response surface methods, mixture designs, and screening designs. Focuses on various treatment structures for designed experimentation and the associated statistical analyses. Use of statistical software.