This course shows how to do high quality data science, one of the fastest, most impactful areas in all of academia, industry, government, and elsewhere. Without overwhelming students with math, we give students the deep intuition behind the theories of inference underlying most statistical methods. We cover how new approaches to research methods, data analysis, and statistical theory are developed so students can understand not merely the methods we teach but new ones that will undoubtedly be invented after this class is over. We also show how it is even easy to conceive original approaches and new statistical methods when required. The specific models we introduce are chosen based on students' research topics. In past years, this has included models for discrete choice, rare events, causal inference, event counts, ecological inference, time series cross-sectional analysis, compositional data, causal inference, and case-control designs.
