Undergraduate | Fall 2017
There are three general goals for students in this course. The first is to help students see the usefulness of dynamic, interactive data analytics for social science in particular. Understanding social relations is a complex task, and computers and code can be very important aids in tackling some of these challenges.
The second goal is to educate students on how to be skeptical consumers and users of quantitative information. There are many opportunities to either mangle or mistake messages in data visualizations. We will study clear and poor examples of communicating information to an audience, and discuss the rules that can help guide the creation of useful summaries of potentially complicated data. Having Big data or wielding random forest algorithms does not mean that inferences are clear, easy or uncontroversial.
The final goal of the class is to begin to empower students to use computers and code to collect their own data, particularly from the web, and produce clear and informative visualizations. Students will be exposed to introductory lesson in R, for munging and plotting data, and Python for web scraping. Along the way, students will learn some command line tools (bash) and be introduced to html and markdown.