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

Course List

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
STAT 280	Statistical Methods
DSCI 352	Analytics I: Predictive Models
ECON 361A	Introductory Econometrics
PSYC 360A	Advanced Statistics for Psychology
SOCG 364	Quantitative Research Methods and Analysis
Any two DATA courses numbered 300 or higher 1		6
Take one course from the following list of choices:		3
Any additional DATA course numbered 300 or higher
ECON 462	Advanced Economic Analysis
PSCI 490	Advanced Research Methods in Political Science
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.

Data Science Program

Stephen Davies, Program Coordinator, Department of Computer Science

Affiliated Faculty

Christopher J. Garcia, College of Business
Debra L. Hydorn, Department of Mathematics
Robert S. Rycroft, Department of Economics
Prashant Chandrasekar, Department of Computer Science
Jessica Zeitz Self, Department of Computer Science