The need for workers trained in the science of data analysis continues to grow in industry, government, and academia. This need spans many fields and applications: national security applications (including real-time monitoring of internet trends), environmental applications of climate modeling over space and time, medical and genomic applications that use electronic medical records to correlate demographics, genetic data and clinical outcomes over millions of individuals, and manufacturing with real-time monitoring of features over a variety of processes to both troubleshoot and optimize manufacturing. 

The Master of Science in Statistics program at the University of Colorado Denver provides the training necessary to succeed in real-world analysis of data. The degree program is designed to ensure students acquire fundamental statistical knowledge while having hands-on experience in the application of state-of-the-art statistical methods—all while collaborating with world-class researchers. The program emphasizes project-related experiences, helping students to further develop skills in programming, data wrangling, data analysis, interpretation, and presentation in a more realistic environment. The degree program is highly flexible depending on student interest. Students can select from a broad range of electives focusing on different areas of mathematics and statistics or pursue electives in computer science, economics, business, or geography. Alternatively, students can choose to pursue training focused in a specific application area of statistics.

Whatever specialization students choose, graduates with a statistics degree will be prepared for a multitude of careers.

The MS in Statistics requires students to complete 30 hours of accepted coursework and a capstone project. The coursework is organized into four components: 1) core courses, 2) statistics-related electives, 3) other electives, and 4) capstone project. The capstone project is developed within the structure of a student-centered, research-focused course. Full-time students take approximately two years to complete the MS degree.

The degree requires students to complete 15 credit hours through five required courses related to probability, statistical theory, regression, consulting, and the capstone project. Students must complete an additional 15 credit hours related to elective courses, which is generally five graduate courses. For the elective courses, three must be statistics-related while two others are more general (though they are typically math-related courses).

These degree requirements are subject to periodic revision by the academic department, and the College of Liberal Arts and Sciences reserves the right to make exceptions and substitutions as judged necessary in individual cases. Therefore, the College strongly urges students to consult regularly with their Statistics faculty advisor to confirm the best plans of study before finalizing them.