The minor in Data Science teaches principles and builds skills in the science of how and why we use data. It is an attractive option that can enhance the credentials for students in a wide variety of domains. Decision making across all levels is increasingly shifting away from subjective human judgment and expert opinion and is being replaced by superior evidence-based approaches driven by data and analytical models. Data Science is the discipline concerned with gathering and manipulating large volumes of data, developing statistical models to gain critical insights from it, understanding the behavior of complex systems through simulation, and making non-trivial decisions optimally, often in response to quickly changing conditions. The minor in Data Science is designed to provide students with the fundamental coursework to succeed in this area.
Minor Requirements
| Code | Title | Credits |
|---|---|---|
| DATA 101 | Introduction to Data Science | 3 |
| DATA 219 | Foundations for Data Science | 3 |
| Take one course from the following list of five courses: | 3 | |
| Statistical Methods | ||
| Analytics I: Predictive Models | ||
| Introductory Econometrics | ||
| Advanced Statistics for Psychology | ||
| Quantitative Research Methods and Analysis | ||
| Any two DATA courses numbered 300 or higher 1 | 6 | |
| Take one of the following: | 3 | |
Any additional DATA course numbered 300 or higher | ||
| Advanced Economic Analysis | ||
| Total Credits | 18 | |
- 1
STAT 320 Applied Regression Analysis may be substituted for one of the 300-level DATA courses in order to meet this requirement.