This course is focused on how to answer questions effectively using quantitative data. By the end of the course, students will be able to recognize different types of questions (e.g. descriptive, causal, and predictive questions), have an understanding of what methodological approaches are most appropriate for answering each type of question, be able to design and critically evaluate data analysis plans, and understand how to tailor their presentation of results to different audiences.
In small teams, students will do their own data science project under close supervision. The process will include cultivating answerable questions, designing approaches for creating statistical features and variables, thinking critically about possible interpretations of results, vetting data stories for logical fallacies, and presenting results to non-technical audiences. This course assumes comfort with statistics and data manipulation/analysis in R or Python.