Katie Coburn

Katie Coburn is a Lecturer in the Department of Statistics and Applied Probability (PSTAT) at the University of California, Santa Barbara (UCSB), based in South Hall 5524. She holds a B.S. in Psychology from San Jose State University (2011) and a Ph.D. in Quantitative Psychology from the University of California, Merced (2018), advised by Dr. Jack L. Vevea. Her work focuses on statistical pedagogy, quantitative methodologies, and meta-analysis.

Dr. Coburn has over nine years of teaching experience, with a strong track record in courses like Probability and Statistics (PSTAT 120A/B/C), Statistical Machine Learning (PSTAT 131/231), and Data Science. She consistently earns high student evaluations, averaging 4.5/5 at UCSB and 5.25/6 at Northwestern University. Notable accolades include the Outstanding Teaching Award at UC Merced (2015-2016).

Her contributions include the weightr R package (2015) and associated Shiny app for meta-analytic methods. She has taught workshops on statistical bootcamps and Shiny apps, emphasizing practical data science skills. Her pedagogical focus extends to mentoring in statistics education, as seen in her PSTAT 190 course on Teaching and Mentoring Statistics.