Degree Specializations
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Students in the program have the option to specialize in one of two tracks: Statistics and data science, or a customized educational plan.
Statistics and Data Science Specialization
This track enables students to develop the foundational tools needed to analyze and interpret data, including complex and high-dimensional datasets. Students have the opportunity to take coursework in probability, statistics, data science theory, statistical and data science applications, and professional development and collaboration skills.
In addition, students will have the opportunity to participate in the department鈥檚 Laboratory for Interdisciplinary Statistical Analysis (LISA), where they gain valuable collaboration skills and foster relationships with faculty and industry professionals.
The specialization in statistics and data science includes the following required courses:
For more information, see our course catalog in and .
Customized Specialization
Students can forge their own path with a customized educational track based on their own interests. Many students choose to capitalize on the department鈥檚 numerous strengths, including computational mathematics, statistics and data science, physical applied mathematics, mathematical biological and social sciences, and mathematical geosciences.
Such specializations should be designed with the MS director within the first year of the program.
An example of a student鈥檚 specialization in financial mathematics may include the following courses:
- APPM 5530: Stochastic Analysis for Finance
- STAT 5100: Markov Processes, Queues and Monte Carlo Simulation
- APPM 5600 Numerical Analysis I (4000-level prerequisite coursework strongly recommended)
- APPM 5610 Numerical Analysis II (4000-level prerequisite coursework strongly recommended)
- STAT 5000: Statistical Methods and Applications I and/or STAT 5010: Statistical Methods and Applications II
- STAT 5540: Intro to Time Series
鈥淚 was able to work hands-on with interesting Climatology research right away in my second year under Dr. Will Kleiber. The PMD program was designed so that I could learn the fundamentals and theory in my first year, and then specialize and apply everything in my second year. I really wanted to focus on Spatial Statistics and Statistical Learning applied to Atmospheric Modeling, and that is exactly what I got to do. It was impactful not just for me as a student, but as an emerging applied Statistician and Data Scientist as well.鈥
Laurette Hamlin
Program alumnus
Senior Systems/Data Analyst