The MSSP program requires the successful completion of eight courses (32 credits), including five core courses and three electives. These courses are designed to provide a foundational sequence of statistics courses designed to reinforce and extend your quantitative background while providing essential instruction in statistical theory and analytic methodology.
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Core courses
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GRS MA 675 & 676 – Statistics Practicum I & II
- More Information on the Practicum can be found here
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GRS MA 677 – Conceptual Foundations of Statistics
- This course is designed specifically for graduate students with quantitative backgrounds. The goal of the course is to provide an accelerated introduction to key topics in probability, mathematical statistics, linear modeling, time series, and non-parametric statistics.
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GRS MA 678 & 679 – Applied Statistical Modeling & Applied Statistical Machine Learning
- In the first semester, emphasis is placed on classical topics that form the core of the working statistician’s toolbox, while in the second semester, the focus broadens to introduce students to a variety of topics in modern statistical machine learning and data mining.
Electives
- 1 statistics elective at the level of 500 or above
- 2 course electives from statistics or a complementary discipline at the level of 500 or above
Elective requirements may be fulfilled through a combination of graduate-level courses in the Department of Mathematics and Statistics and/or courses in other related disciplines. Electives must be approved by a statistics advisor.
Full-time students can complete the program in as little as 1 year (2 semesters), though many choose to complete their requirements in 1.5 years (3 semesters). Part-time students typically complete the program in 2 years (4 semesters).
Course Descriptions
