The Art of Numbers
As data sets get larger and larger, visual tools for exploring them become even more important. "The Art of Numbers" focuses on the insight into quantitative information offered by graphs, tables, charts, maps, and other illustrations. The course explores which graphical tool(s) are best for communicating what kinds of data, and why? Ideas about causality, approximation, statistical significance, credibility, and dimensionality are addressed by analyzing real data and their display. Examples are drawn from epidemiology, astronomy, sports, social-science, finance, geography, politics and economics.
Approximately one-half of the course material focuses on web, interactive, and live presentations of data. Textbooks include classic work by Edward Tufte.
Wondering whether to take this course or CS171?
CS171 is aimed at teaching the principles of visualization and then appliying those principles to programming skills that allow for the creation of web-based, interactive visualizations.
EMR19 is focused more on the connections between visualization approaches and principles for a variety of applications in different fields (e.g. medicine, geography, economics, astronomy, etc.). EMR19 spends more time on historical examples, and connections to art, psychology and aesthetics. There is only basic programming in EMR19.
Both courses require a final project, and the main difference in that requirement is the level of programming involved.
Students with a strong technical background should consider CS171. Please contact Prof. Goodman or Prof. Pfister if you need more information — we will be happy to help you choose between our courses.
Emily Xie '12 (final project):
I took EMR 19 my senior spring as an HAA concentrator, and it easily became one of my favorite GenEd courses during my time at Harvard. Professor Goodman was an incredible and supportive professor, and the material was thought-provoking and fascinating. The problem sets were also pretty fun and painless. The broad exposure to different data visualization tools and theoretical concepts proved really useful and applicable for me—I even ended up applying what I had learned to build a big data dashboard at my first job.
Overall, I strongly recommend this course. If you decide to enroll, be sure take the time to think through your final project, as it really allows a rare opportunity to get creative and learn something new in a self-directed manner!