Ethan Christopher Brown

Fields of Interest:

Research methods
Education research
Decision-making under uncertainty
Power analysis
Open science

Education:

PhD: 2019, University of Minnesota, USA

Bio:

Ethan C. Brown researches and teaches social science research methods and statistical cognition. The advantage of research being a flawed human process is that there is a lot of need for improvement and many ways to contribute. Ethan firmly believes that every student and aspiring researcher has the potential to find these gaps and participate in their way in the research conversation.

As the former Associate Director of the Research Methodology Consulting Center at the University of Minnesota, Ethan consulted on varied research projects, designed and led hands-on professional development short courses in research methods, and taught research methods courses.

He is an active member of the larger open science community and works to connect researchers to practical solutions to make their research more credible and reproducible.

His analysis work includes leading the Tracing Pathways project for the Minnesota Statewide Longitudinal Educational Data System (SLEDS) and supporting numerous grants, including studies of illegal baitfish release, elder fraud, and conceptual understanding of biology.

As an education researcher, the classroom also serves as Ethan’s laboratory for learning how people think about statistics and make decisions amidst uncertainty.

He believes we are already intuitively acting as statisticians in everyday life, and he has built a program of research studying how people incorporate—or fail to incorporate—sample size and strength of evidence in various contexts, which he has studied using both qualitative and quantitative methodologies. His recent research builds on the sample size research by developing frameworks and tools to support researchers with study design and power analysis. In our increasingly algorithmically-driven world, his goal is to build on cognitive science, educational research, and natural human intelligence to make statistics, and critical awareness of statistics’ limitations, accessible to all.

Courses: