Master of Science in Statistics
Preparation
Before entering the program, the student should have completed the following.
- 3 semesters of calculus
- 1 semester of linear algebra
- 2 semesters of calculus-based probability theory
- Working knowledge of a programming language
Students lacking some of the above undergraduate coursework may be admitted conditionally
and may make up this coursework during the first year of the program (these courses
will not be counted toward the degree course requirements).
Adviser
Required Courses
The program requirements can be found in the course catalog.
Degree Learning Outcomes
Listed below are the applicable Degree Learning Outcomes (DLOs) for this degree.
- Describe and formulate statistical hypotheses based on scientific questions at hand.
- Choose and apply correct methods and modeling approaches for data analysis.
- Evaluate multiple approaches for a given problem and data set using statistical or computational tools such as cross validation and/or Monte Carlo simulations.
- Evaluate the fit of a statistical model and improve the fit by methods such as variable transformations and interactions as appropriate.
- Interpret statistical inferences in terms of real-life problems.
- Appraise and apply a new method in the literature for problem solving and data analysis as appropriate.
- Be able to critically evaluate, select, and use appropriate statistical software.
- Communicate and report statistical findings orally and in writing to both statisticians and other quantitatively oriented scientists.