COURSE CURRICULUM

The Master of Science in Statistics program requires a total of 36 units and is designed to build strong theoretical knowledge, computational skills, and applied expertise in statistical science for careers in industry, government, and research. The program includes 21 units of core courses that provide foundational training in probability theory, mathematical statistics, statistical programming using R, Python, and SQL, data visualization, regression theory, and technical communication in mathematics or computer science, including completion of a Graduate Writing Assessment Requirement course. These core subjects ensure students develop both rigorous mathematical understanding and practical data analysis skills. In addition to the core curriculum, students complete 12 units of electives or may choose a structured specialization in Machine Learning, depending on their academic and career goals. Elective options may include advanced topics such as experimental design, statistical learning, clustering, and other advisor-approved courses that strengthen analytical and computational abilities. The program also requires a 3-unit culminating experience, which can be completed through applied project work, internships, special study, or a combination of an additional elective and a comprehensive written examination covering probability, mathematical statistics, and regression analysis. This structure allows students flexibility in tailoring their learning path while ensuring mastery of essential statistical concepts and methods. Overall, the program integrates theory, computation, and real-world application to prepare graduates for professional roles as statisticians and data scientists capable of solving complex problems and supporting data-driven decision-making across a wide range of industries.