M.S. in Applied Statistics
| Code | Title | Credits |
|---|---|---|
| Required | ||
| 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: | 9 | |
| Topics In Applied Statistics | ||
| Survival Analysis | ||
| Longitudinal Data Analysis | ||
| Time Series | ||
| Multivariate Data Analysis | ||
| Data Mining | ||
| Advanced Statistical Programming Using SAS | ||
| Statistical Programming Using R | ||
| Applied Bayesian Methods | ||
| Statistical Consulting | ||
| Categorical Data Analysis II | ||
| Statistical Methods for Observational Studies | ||
| Statistical Methods in Business and Finance | ||
| Applied Marketing Analytics | ||
| Statistical Design and Analysis of Clinical Trials | ||
| Foundations of Bioinformatics | ||
| Foundations of Data Science | ||
| Applied Statistical Machine Learning | ||
| Data Visualization | ||
| Internship In Applied Statistics | ||
| Thesis I | ||
| Thesis II | ||
| Total Minimum Credits Required | 33 | |
To track their individual degree progress, students are advised to access their Degree Audit via RamPortal and consult their Graduate Coordinator. For more information, visit the Degree Audit FAQ webpage.
The following is a sample suggested course sequence for this program; course offerings and availability are not guaranteed. Students should consult their academic advisor with any questions.
Non-Thesis Option
| Year One | ||
|---|---|---|
| Semester One | Credits | |
| STA 503 | Introduction to R | 1 |
| STA 505 or STA 504 |
Mathematical Statistics I or Mathematical Statistics I with Calculus Review |
3-4 |
| STA 511 | Intro Stat Computing & Data Management | 3 |
| Credits | 7-8 | |
| Semester Two | ||
| STA 506 | Mathematical Statistics II | 3 |
| STA 512 | Principles of Experimental Analysis | 4 |
| Credits | 7 | |
| Summer | ||
| STA 601 | Internship In Applied Statistics (Optional) | 3 |
| Elective (Optional) 1 | 3 | |
| Credits | 6 | |
| Year Two | ||
| Semester Three | ||
| STA 507 | Introduction to Categorical Data Analysis | 3 |
| STA 513 | Intermediate Linear Models | 4 |
| Credits | 7 | |
| Semester Four | ||
| STA 514 | Modern Experimental Design | 3 |
| Elective (Optional) | 3 | |
| Credits | 6 | |
| Total Credits | 33-34 | |
- 1
Can take more than one elective (any STA course numbered STA 531 or above) each summer.
Thesis Option
| Year One | ||
|---|---|---|
| Semester One | Credits | |
| STA 503 | Introduction to R | 1 |
| STA 505 or STA 504 |
Mathematical Statistics I or Mathematical Statistics I with Calculus Review |
3-4 |
| STA 511 | Intro Stat Computing & Data Management | 3 |
| Credits | 7-8 | |
| Semester Two | ||
| STA 506 | Mathematical Statistics II | 3 |
| STA 512 | Principles of Experimental Analysis | 4 |
| Credits | 7 | |
| Summer | ||
| STA 601 | Internship In Applied Statistics (Optional) | 3 |
| Credits | 3 | |
| Year Two | ||
| Semester Three | ||
| STA 507 | Introduction to Categorical Data Analysis | 3 |
| STA 513 | Intermediate Linear Models | 4 |
| STA 609 | Thesis I | 3 |
| Credits | 10 | |
| Semester Four | ||
| STA 514 | Modern Experimental Design | 3 |
| STA 610 | Thesis II | 3 |
| Credits | 6 | |
| Total Credits | 33-34 | |
