May 08, 2024

2023-2024 Undergraduate Catalog

Data Analytics, Minor

About the Minor

Data Analytics is a dynamic field in which new approaches, content, and techniques for manipulating and analyzing data are constantly being introduced to answer questions such as “what does social media tell us about mental health?” and “how much will the global temperature increase in ten years?”. Data Analytics uses tools from Computer Science and Statistics to analyze large amounts of raw data to discover useful relationships and to inform decisions. Data Analytics is an important tool for any field that generates and consumes large amounts of data.

This interdisciplinary minor on Data Analytics is open to students from all majors, although it is expected that most students will draw from Biology, Business Administration, Computer Science, Math, Psychology, Physical Therapy, and Public Health.

Requirements

24 credits/ six courses

The University policy specifies that a maximum of two courses may double count toward a major and minor.

Core Courses

MA 141 Elementary Statistics & MA 242 Intermediate Statistics

MA 342 Mathematical Statistics I & MA 343 Mathematical Statistics II

CS 222 Introduction to Data Science with Python (with CS22L Lab)

CS 229 Introduction to Data Science with R

CS 277 Introduction to Data Mining

at Most One Elective Course from:

MA 341 Probability
CS 341 Computer Ethics
CS 377 Advanced Data Mining

at Least One Elective Course from:

BA 348 Marketing Research (4 Credits) *has BA340 as an additional prerequisite
BI 338 Bioinformatics (4 Credits)
PY 142 Research Methods (4 Credits)
PBH 250 Epidemiology: The Science of Public Health (4 Credits)
BA 353 Business Analytics (4 Credits)
CS 222 Introduction to Data Science with Python (with CS 222L Lab) (4 Credits)
OR
CS 229 Introduction to Data Science with R (4 Credits)
(whichever one of these courses that was not taken as a core course.)