Advanced Statistics with Impact Mindset (aSWIM)

This course introduces students to advanced statistical methods in the context of applications with high social impact. It helps students learn about the technical aspects of these methods, as well as the critical statistical thinking skills necessary to relate methods to applied contexts. It also includes horizontally- and vertically-integrated components to support communication skills across disciplines and experience levels.
In this course, advanced statistical methods are methods that follow or build on multiple linear regression. The specific technical topics will vary by semester, but will include multilevel/mixed effect/hierarchical models, and generalized linear models (such as logistic or Poisson regression), and may include other topics such as spatial modeling, networks, causal inference, mediation analysis, or latent class analysis. The methods will be introduced in the context of research data related to some subset of disparities in policing, legal cynicism and violence, global health, STEM student success, segregation, inequality in access to nature, political beliefs and extremism, and disparities in college sex and dating. Students from both technical and applied majors will work together in horizontally-integrated teams to deepen content learning and support learning collaboration across disciplines.