Interdisciplinary Data Science
The Interdisciplinary Data Science Minor provides students with real-world skills in understanding and analyzing data. Students will learn basic hacking skills, will develop necessary statistics skills, and will learn to apply these skills through substantive quantitative subject-matter focused coursework.
Minor Requirements
Minors require a minimum of
9 credits of upper-division (300-400 level) coursework
- For example, if ECON 262 or PSY 210 are used to satisfy the Mathematics/Statistics Core, then the two courses from the Quantitative Subject Matter Core must be upper division
Required Courses
Computer Science Core (6 credits)
Mathematics and Statistics Core (3 credits)
Complete one of the following courses:
ECON 262 | Principles of Statistics II | 3.00 |
MATH 352 | Probability and Statistics | 3.00 |
PSY 210 | Introduction to Statistical Methods | 3.00 |
STAT 391 | Applied Statistics for Biological Sciences | 3.00 |
Quantitative Subject Matter Core (6 credits)
Complete two courses from the following:
BIOL 416 | Bioinformatics | 3.00 |
BIOL 441 | Field Ecology | 4.00 |
CHEM 445 | Organic Spectroscopy and Structure Determination | 4.00 |
CRJ 301 | Research Methods in Criminal Justice | 3.00 |
CRJ 302 | Quantitative Applications in Criminal Justice | 3.00 |
ECON 262 | Principles of Statistics II | 3.00 |
ENV 480 | Geographic Information System for Environmental Management | 4.00 |
FIN 301 | Principles of Managerial Finance | 3.00 |
IS 301 | Management Information Systems | 3.00 |
MGT 391 | Quantitative Analysis | 3.00 |
PSY 240 | Introduction to Research Methods | 3.00 |
PSY 375 | Advanced Undergraduate Research | 3.00 |
PSY 481 | Principles of Psychological Assessment | 3.00 |
SOC 403 | Techniques of Social Research | 3.00 |
STAT 413 | Statistical Experimental Design | 3.00 |
Note: The Quantitative Subject Matter Core is not a complete list; courses meant to satisfy this requirement should be screened by a faculty member with expertise in the field to ensure that the content is sufficiently data-driven/quantitative in scope.
Data Science Capstone (3 credits)
Complete one of the following courses:
MATH 489 | Advanced Mathematical Topics | 3.00 |
STAT 488 | Senior Research Project in Statistics | 3.00 |