Philosophy

Teaching is something that I enjoy and take very seriously. As a professor, I realize the trust that students put in me to teach them how to be a successful statistician. As a teacher, my goal is not to stimulate a students mind for a lecture, day or even a single semester. Rather, I strive to give students the proper tools to facilitate a lifetime of learning.

I teach a range of undergraduate and graduate statistics courses, including introductory data analysis, regression, statistical learning, and the analysis of correlated and spatial data. Across courses, my goal is to help students develop both strong conceptual understanding and practical data-analytic skills that prepare them to work effectively with real, messy data.

My teaching emphasizes active learning, computation, and interpretation. Students regularly engage with authentic datasets, learn to communicate statistical results clearly, and use modern tools such as R and machine-learning workflows to explore, model, and draw conclusions from data. I strive to create an inclusive and supportive learning environment that encourages curiosity, critical thinking, and confidence in working with quantitative information.