This course will provide students with fundamental principles of and practical experience in presenting data in a visual form for communication and analysis. The class will cover collection of data, management of data for visualization, creating a workflow for visualization, collaboration with designers and coworkers, and examples of visualization which communicates effectively. For students of Public Policy, mastering the skills of persuasive communication with empirical evidence is essential, and visual communication can be a powerful tool in that skillset.
The course is comprised of four core modules: principles/fundamentals of design and visualization and review of visualization programming in Excel, STATA, and R/ggplot. In each of those modules, students will learn how to translate quantitative data (or coded qualitative data) into visualizations for examining patterns which reveal insights about the world. At the end of this class, students should have a baseline understanding of visualization for use in their own work and development of their own skills. The course is graded credit/no credit (pass/fail), with a course-long data visualization portfolio project. Students are not expected to have experience or prior knowledge of software or principles, but a baseline understanding of statistical concepts is recommended.