Data Science and Statistics
The Data Science and Statistics Minor
T. Arnold (Statistics)
Y. Jiang (Computer Science)
P. Kvam (Statistics)
M. Lowder (Psychology)
K. Nolin (Chemistry)
Lilla Orr (Data Science and Statistics)
S. Spera (Geography and the Environment)
L. Tilton (Digital Humanities)
M. Yang (Biology)
The minor in Data Science and Statistics prepares students to address the challenges of collecting, understanding and presenting structured and unstructured data from a variety of different domains and contexts.
The program takes an interdisciplinary approach built around five specific skills needed to achieve these goals:
Developing proficiency in data-oriented programming
Understanding probability theory and statistical inference
Understanding which methods are appropriate for which kinds of data analysis,
Ability to identify and address the ethical and privacy concerns regarding data analysis, and
Gaining experience applying techniques and presenting results within the context of an application domain.