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.

Degree 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

Computer Science Core (6 credits)

CS 135Computer Science I

3.00

CS 202Computer Science II

3.00

Mathematics and Statistics Core (3 credits)

Complete one of the following courses:
ECON 262Principles of Statistics II

3.00

MATH 352Probability and Statistics

3.00

PSY 210Introduction to Statistical Methods

3.00

STAT 391Applied Statistics for Biological Sciences

3.00

Quantitative Subject Matter Core (6 credits)

Complete two courses from the following:
BIOL 416Bioinformatics

3.00

BIOL 441Field Ecology

4.00

CHEM 445Organic Spectroscopy and Structure Determination

4.00

CRJ 301Research Methods in Criminal Justice

3.00

CRJ 302Quantitative Applications in Criminal Justice

3.00

ECON 262Principles of Statistics II

3.00

ENV 260Environmental Measurement and Analysis

4.00

ENV 480Geographic Information System for Environmental Management

4.00

FIN 301Principles of Managerial Finance

3.00

IS 301Management Information Systems

3.00

MGT 391Quantitative Analysis

3.00

PSY 240Introduction to Research Methods

3.00

PSY 375Advanced Undergraduate Research

3.00

PSY 481Principles of Psychological Assessment

3.00

SOC 403Techniques of Social Research

3.00

STAT 413Statistical 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 489Advanced Mathematical Topics

3.00

STAT 488Senior Research Project in Statistics

3.00