Data analytics is an interdisciplinary minor that combines statistics and computer science, preparing students to understand how to ask questions and present answers about a world in which exponentially growing amounts of quantitative data are becoming available. The minor trains students to organize and assemble large data sets, process them, and use them to describe and answer questions about the world in all of its complexity. In the context of the Ursinus core curriculum, the minor asks students to consider the question, “How can we understand the world?”

Requirements for Data Analytics Minor

A minor in data analytics consists of 24 credits, with 16–20 credits in required courses. Required courses are as follows:

Programming courses (prerequisites for DATA classes)

• A two- to four-credit course focusing on R programming. DATA-150 satisfies this requirement. Other courses will be accepted for this requirement with the permission of the data analytics coordinator.
• A two- to four-credit course focusing on Python programming. CS-170Q satisfies this requirement. Other courses will be accepted for this requirement with the permission of the data analytics coordinator.

Data Classes

• DATA-201
• DATA-202
• DATA-301

In addition, data analytics minors must complete between four to eight elective credits to reach 24 credits in the minor. The following courses will satisfy the elective requirement:

• CS-173
• CS-377
• CS-477
• DIGS-200
• DATA-350
• No more than one of the following courses, which require data gathering, description, and statistical analysis: ANSO-200, BIO-359, CHEM-315/315L, HEP-261W, NEUR/PSYC-432W, POL-300, STAT-242, STAT-243W, or ECON-300Q.
• Honors or research or an independent study in any discipline that involves significant data analysis may also count towards the minor, with the permission of the data analytics coordinator.