Interdisciplinary Minor

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

Application Process

Interested in pursuing data science? Email us at datasci@davidson.edu. If you wish to declare a data science minor, you must first complete the . You should do this in discussion with the department chair, Prof. Laurie Heyer (Mathematics and Computer Science) at laheyer@davidson.edu as early as possible, and no later than the fall semester of senior year.

Courses You Might Take

CSC 110

An introduction to methods of data science, including computer programming, data visualization, and statistical analysis. Students will collect, process, analyze, and present data in order to expose and help each other understand issues of social and economic justice. All work will be done in R, a freely available data analysis software package.

DIG 210

This course explores the role of data and databases in contemporary culture, with an eye toward understanding how data shapes the way we perceive-and misperceive-the world. After historicizing the origins of modern databases in 19th century industrialization and census efforts, we will survey our present-day data landscape, considering data mining, data visualization, and database art.

SOC 392

This class will prepare you as a future producer and evaluator of high-quality quantitative research—whether as a social scientist, a decision-maker in a corporate setting, or a designer and evaluator of social policy. Extending theoretical concepts from introductory Social Statistics, this class provides students with hands-on quantitative analysis experience using existing quantitative research.

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