I am a survey statistician who develops estimation techniques that combine complex survey data with big data sources. Whether it’s to estimate official statistics, related to canopy cover or occupational statistics, or to assess the impact of voter ID laws, I enjoy creating methods to learn from data. I also enjoy teaching my students how to learn from data and introducing them to R (an open source statistical software program). As a firm believer that undergraduate research enhances the educational experience, I involve students in my own work and co-chair two national programs: the Undergraduate Statistics Project Competition and the Electronic Undergraduate Statistics Research Conference.
PhD in Statistics, 2011
Colorado State University
Masters in Statistics, 2008
Colorado State University
BA in Mathematics, 2006
Saint Olaf College
I enjoy helping my students develop their abilities to think statistically, to understand variability, and to draw sound conclusions from data. The statistical software package R/RStudio plays a prominent role in most of my classes with the students learning a reproducible workflow through creating R Markdown reports.
Spring 2019 Courses:
Fall 2018 Courses:
In many of my research projects, I develop new estimators for complex survey data using modern modeling techniques such as penalized splines, elastic net regression, and regression trees. For several years, I have partnered with the Forest Inventory and Analysis Program to estimate forestry quantities by combining complex sample data with remotely sensed data. For 2016 – 2017, I was an ASA/NSF/BLS Research Fellow and explored statistical learning techniques for estimation and imputation at the Bureau of Labor Statistics.
Current Projects:
Publications: