DIDA 380BAdvanced Data Modeling

Catalog

Modeling the relationships between variables is a fundamental part of data analysis. In this course, students will receive a broad introduction to data models, how to choose what kind of model is an appropriate fit for different types of data, and how to assess the validity and fit of a model. Topics may include linear and logistic regression, survival analysis, time series analysis, spatial regression, and causal inference. The course is primarily project-based, and emphasis will be placed on applications rather than mathematical foundations. All content will be taught in R, but no prior R programming experience is required.