Track in Statistics and Data Science
Track in Statistics and Data Science
Students will have the option to specialize in Statistics and Data Science. This specialization is meant to give students the foundational mathematical and computational skills for analyzing data, including complex and high dimensional datasets. In particular, students have the opportunity to take coursework in probability, statistics, and data science theory, statistical and data science applications, and professional development and collaboration skills. The table below provides a partial list of courses available to professional MS students in the Department of Applied Mathematics.
Students interested in statistics and data science have the opportunity to complete their Culminating Experience (CE) project with one of our faculty experts in statistics and data science. Students may also complete their CE through the department’s Laboratory for Interdisciplinary Statistical Analysis (LISA). The most natural way to do this would be to produce a written report and presentation of a collaborative project from STAT 5680 Statistical Collaboration or STAT 5690 Advanced Statistical Collaboration.
| List of Courses. For more information, see the course catelog in STAT and APPM. | |
|---|---|
| STAT 5520 Introduction to Mathematical Statistics* |
Probability, Statistics, and Data Science Theory
|
STAT 5530 Mathematical Statistics (for advanced stats and data science students) | |
| STAT 5540 Introduction to Times Series | |
| STAT 5100 Markov Processes, Queues, and Monte Carlo Simulations | |
| STAT 5230 Stochastic Analysis for Finance | |
| STAT 5650 Randomized Algorithms | |
| APPM 5490 Theory of Machine Learning | |
| APPM 5515 High Dimensional Probability for Data Science | |
| APPM 6560 Measure-Theoretic Probability | |
| STAT 5000: Statistical Methods and Applications I* |
Statistical and data science applications |
| STAT 5010: Statistical Methods and Applications II* | |
| STAT 5610 Statistical Learning* | |
| STAT 5430 Spatial Statistics | |
| STAT 5630 Computational Bayesian Statistics | |
| STAT 5400 Advanced Statistical Modeling | |
| APPM 5510 Data Assimilation in High Dimensional Dynamical Systems | |
| STAT 5720 Deep Learning | |
| STAT 5700 Philosophical and Ethical Issues in Statistics |
Professional development and Collaboration skills |
| STAT 5680 Statistical Collaboration | |
| STAT 5690 Advanced Statistical Collaboration (2-credits) | |
| APPM 6930 Professional Master's Culminating Experience | |
| * required for the track in statistics and data science | |
This PDF contains a sample program representing one possible scenario for successfully completing the degree with a Statistics and Data Science specialty. Other scenarios are possible.