M.S. in Applied Statistics - Data Science Concentration
College of the Sciences and Mathematics
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| STA 502 | Introduction to Python for Statistics and Data Science | 1 |
| STA 503 | Introduction to R | 1 |
| STA 505 | Mathematical Statistics I | 3-4 |
| or STA 504 | Mathematical Statistics I with Calculus Review | |
| STA 506 | Mathematical Statistics II | 3 |
| STA 507 | Introduction to Categorical Data Analysis | 3 |
| STA 511 | Intro Stat Computing & Data Management | 3 |
| STA 512 | Principles of Experimental Analysis | 4 |
| STA 513 | Intermediate Linear Models | 4 |
| STA 514 | Modern Experimental Design | 3 |
| Electives | ||
| Select 9 credits from the following list of electives (other STA electives may be substituted with permission of the Program Director): | 9 | |
| Time Series | ||
| Data Mining | ||
| Advanced Statistical Programming Using SAS | ||
| Statistical Programming Using R | ||
| Statistical Methods in Business and Finance | ||
| Applied Marketing Analytics | ||
| Foundations of Bioinformatics | ||
| Foundations of Data Science | ||
| Applied Statistical Machine Learning | ||
| Data Visualization | ||
| Internship In Applied Statistics | ||
| Thesis I | ||
| Thesis II | ||
| Database Systems Concepts | ||
| Total Minimum Credits Required | 34 | |
