Introducing Data Science Elements through Parallel Courses in Statistics and Computing

Eric Reyes & Megan Heyman (Rose-Hulman Institute of Technology)


In the fall of 2017, Rose-Hulman Mathematics and Computer Science departments jointly launched a minor in Data Science. The popularity of the minor has already resulted in increased enrollment in required statistics electives. Specifically, all students receiving the minor take an introductory course in statistics. With the constraints of the minor, many students also elect to take a course which emphasizes statistical programming. Both the introductory course and the statistical programming course are offered only in the fall. In order to support the new minor, we have aligned these courses to provide a strong Data Science foundation for students electing to take both concurrently. Changes we have made to the courses include assignments and lectures incorporating open-ended questions, increased group work, intensive programming, and data analysis projects. In this session we will highlight these changes as well as discuss how the structures support statistical and computational thinking and communication. Participants will be asked to begin developing a project that could be offered in a future iteration of their course.