Teaching
Teaching Philosophy
The best thing about being a statistician is that you get to play in everyone’s backyard. -John Tukey.
Statistics, at its core, is about communication. Ultimately, my job as a collaborative statistician is to convey a message from data to colleagues, partners, and patients. My primary goal in teaching is to train my students to engage in this process of communication: to understand how to glean knowledge from data and share that knowledge effectively.
I am a passionate and award-winning statistics educator. My pedagogy focuses on developing and leveraging students’ statistical intuition, rather than teaching a suite of procedures, so they are better equipped to enter a rapidly changing world of data science. To do this, I engage students in their own knowledge-building through active learning techniques, judiciously incorporate technology, and use low-stakes assessments encouraging trial and error.
I am committed to meeting students where they are and building biostatistical skills and interest appropriate for their academic goals.
Courses Taught
Course designer and instructor of record.
Introductory biostatistics course for students in Epidemiology PhD and MPH programs.
Primary instructor with Trang Q. Nguyen.
8-week hour-long seminar for masters and doctoral students in mental health. The topic was “Promises and Pitfalls of Prediction Models in Mental Health”.
Graduate Student Instructor
Large, non-calculus-based, cross-disciplinary introductory statistics course. Taught 2-3 weekly lab sessions of 30 students each.
Course Instructors: Jack Miller, Ph.D.; Brenda Gunderson, Ph.D.
Teaching Assistant
Four-week project-based course for political and social scientists interested in mixed modeling. Held daily office hours to assist students with project-based learning.
Course Instructor: Mark Manning, Ph.D.
Teaching Assistant
Two-week lecture series on graphics, data management, modeling, etc., in R. Held daily office hours.
Course Instructor: John Fox, Ph.D.
Graduate Student Instructor
Upper-level undergraduate introductory machine learning course using An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani). Taught weekly lab session for approximately 45 students.
Course Instructor: Liza Levina, Ph.D.
Graduate Student Instructor
First graduate-level regression course for Applied Statistics masters students, using Linear Models with R, 2nd ed. (Faraway). Held weekly office hours and graded homework and exams.
Course Instructor: Brian Thelan, Ph.D.
Undergraduate Teaching Assistant
Senior undergraduate-level introductory biostatistics course for biology and life science majors. Co-taught weekly lab sessions with a graduate TA, graded lab reports.
Course Instructor: Gary Lamberti, Ph.D.