Last updated: 2022-07-23

My research falls under three broad themes: statistics and data science education, statistical modeling, and consulting.

Statistics and data science education

“Data Science in 2020: Computing, Curricula, and Challenges for the Next 10 Years”. Journal of Statistics Education.

“The State of Statistics Education Research in Client Disciplines: Themes and Trends Across the University” (2019). Journal of Statistics Education.

“Life on an Island: Using Peer Consulting in Applied Statistics Courses” (2017). CHANCE: Teaching Statistics in the Health Sciences column.

“Developing a First-Year Seminar Course in Statistics and Data Science” (2016), International Association of Statistics Educators Roundtable Conference Proceedings.

Spatial statistics and statistical modeling

During my PhD work, I developed a kriging model for spatially correlated proportional data using the beta-binomial distribution. Despite the relative mathematical simplicity of the model, it was shown to outperform other options in terms of predictive accuracy.

Articles related to this work include:

“Emerging patterns in multi-sourced data modeling uncertainty” (2016) Spatial Statistics.

“Beta-Binomial Kriging: An Improved Model for Spatial Rates” (2015) Procedia Environmental Sciences.

Since then, I have shifted focus to generalized linear mixed models with a spatial correlation structure, and attempts to improve computational efficiency without sacrificing accuracy. Most recently, Creighton graduate Mark May (2020) completed several simulation studies in this area, and presented his results at the Joint Statistical Meetings.

Statistical consulting

A significant part of my research time is devoted to statistical consulting. Some papers I’ve served as a statistical consultant or co-PI on include: