The Master of Applied Statistics, Plan C, Data Science Specialization emphasizes practical methods in statistics and data science, focusing on applications and computational aspects rather than theory. The goal of this degree is to enable students to start working as data scientists in business, industry, or government immediately after graduation. Students receive a strong background in statistical and business computing while completing this degree. Full-time students complete the M.A.S. degree in less than a year; however, this degree may also be completed part-time, either online or on campus. Students who succeed in the field of data science typically have strong quantitative skills, analytical minds, and like to help others solve problems.
Effective Fall 2021
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| CIS 605 | Business Visual Application Development | 3 |
| CIS 655 | Business Database Systems | 3 |
| STAA 551 | Regression Models and Applications | 2 |
| STAA 552 | Generalized Regression Models | 2 |
| STAA 553 | Experimental Design | 2 |
| STAA 555/STAT 555 | Statistical Consulting Skills | 1 |
| STAA 556 | Statistical Consulting | 2 |
| STAA 561 | Probability with Applications | 2 |
| STAA 562 | Mathematical Statistics with Applications | 2 |
| STAA 565 | Quantitative Reasoning | 1 |
| STAA 577 | Statistical Learning and Data Mining | 2 |
| STAA 578 | Machine Learning | 2 |
| Select from the following: | 3 | |
| Data Visualization Methods | ||
| Computational and Simulation Methods | ||
| Nonparametric Methods | ||
| Analysis of Time Series | ||
| Select from the following electives: | 3-4 | |
| Business Intelligence | ||
| Applied Data Mining and Analytics in Business | ||
| Mixed Models | ||
| Methods in Multivariate Analysis | ||
| Applied Bayesian Statistics | ||
| Program Total Credits: | 30-31 | |
A minimum of 30 credits are required to complete this program.