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Data Science Interdisciplinary Minor

The data science interdisciplinary minor is open to students from all academic divisions who wish to develop skills in using and analyzing data. Such data skills can complement and enhance liberal arts study across a broad range of subject matters and interests.

  • Humanities: The minor provides technical skills that can powerfully complement the writing, creativity and critical analysis encouraged in humanities courses.
  • Social sciences: The minor promotes facility with data supplements and enhances your ability to analyze and understand societal questions and problems.
  • Natural sciences and mathematics: The minor deepens data management skills and can improve quantitative analysis in all major fields.

Learning Outcomes

Whatever your major, a data science minor provides transferable skills that prepare you for further work in data science after Davidson, whether in a masters or Ph.D. program or future employment. Those skills include the following.

  • Understand data and its different forms.
  • Collect and transform data.
    • Obtain data through scraping or mining.
    • Parse and transform data into structures designed for analysis.
  • Draw meaning from data.
    • Visualize data to improve or shape understanding.
    • Statistically analyze data to summarize, draw inference, and make predictions.
    • Discover and characterize patterns in large data sets.
  • Collect, analyze, and present data in an ethically responsible manner (and submit any required documentation for approval by the Institutional Review Board).
  • Communicate effectively about data, methods, and conclusions.


The data science minor consists of six courses: one course in statistics, one course in programming, and four of the approved electives.

Additional information about the data science interdisciplinary minor requirements is available in the College Catalog.

Application Process

If you wish to declare a data science minor you must first complete the application. You should do this in discussion with one of our coordinators, Prof. Laurie Heyer (Mathematics and Computer Science) or Prof. Pat Sellers (Political Science) as early as possible, and no later than the fall semester of senior year.