COURSE CURRICULUM

The Master of Science in Statistics at the University of Colorado Denver is a structured 30-credit graduate program designed to be completed in approximately two years for full-time students and is centered on building strong theoretical and applied expertise in probability, statistical modeling, and data analysis. The curriculum is organized into four components: core courses, statistics electives, other electives, and a capstone project, ensuring both depth in statistical foundations and flexibility for specialization. Students begin with core training in essential areas such as probability, statistical inference, regression analysis, stochastic processes, or statistical consulting, depending on course selection and academic focus. In addition to core requirements, students must complete nine credit hours of statistics-focused electives chosen from advanced topics such as machine learning methods, Bayesian statistics, experimental design, Monte Carlo methods, spatial data analysis, probabilistic modeling, and related areas, allowing them to tailor their studies toward applied statistics, data science, or theoretical probability. A further six credit hours are taken as general electives, which may include additional graduate-level mathematics courses or approved courses from other departments, enabling interdisciplinary academic development. The program culminates in a capstone experience, which requires all students to complete a written project and pass a final oral examination; this may be completed through a master’s thesis, master’s project, or research methods course, depending on the chosen pathway. Students must complete at least 30 credit hours of approved coursework, with a minimum of 24 hours at the graduate MATH 5000 level or above, maintain a cumulative GPA of at least 3.0, and earn no grade below B- in applicable courses. Additional requirements include completing at least 21 credit hours with CU Denver faculty and adhering to transfer credit limits and program timelines, which generally require completion within seven years. Overall, the program is designed to balance rigorous mathematical training with applied statistical practice and research experience.