Teaching Experience

I care most about helping students feel that statistics and computation are things they can use, not things that are done to them. In my classes, I work deliberately to reduce “stats anxiety” by breaking problems into clear steps, connecting every method to a real clinical or research question, and showing how even small pieces of code can answer meaningful questions about health. Many of my learners have minimal coding background, are juggling clinics or labs, and may be first-generation in graduate school. My job is to respect that reality while still holding a high bar for rigor, reproducibility, and ethical use of data.

In practice, I teach through worked case studies drawn from dentistry, microbiome research, and human toxicology. We move back and forth between intuition, equations, and code, so students see how a method behaves, what its assumptions are, and how to communicate results responsibly. I emphasize transparent workflows, well-documented code, and readable visualizations, because I want students to leave not only with grades, but with reusable analysis habits they can take into their own projects and careers.