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

 
 
 
 
 
University of Pennsylvania Perelman School of Medicine
BSTA 6100: Biostatistical Methods for Epidemiology
University of Pennsylvania Perelman School of Medicine
August 2024 – Present

Course designer and instructor of record.

Introductory biostatistics course for students in Epidemiology PhD and MPH programs.

 
 
 
 
 
Statistical Horizons
SMART Designs for Developing Adaptive Interventions
August 2024 – Present

A 4-day synchronous virtual seminar series on designing and analyzing sequential, multiple-assignment, randomized trials to build effective adaptive interventions. Watch the first hour of the 2024 seminar on YouTube!

Next session begins July 8, 2025. Register here.

 
 
 
 
 
Johns Hopkins Bloomberg School of Public Health
Seminar on Statistical Methods for Mental Health
Johns Hopkins Bloomberg School of Public Health
September 2022 – October 2022 First Term, AY 2022-2023

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”.

 
 
 
 
 
University of Michigan
STATS 250: Introduction to Statistics and Data Analysis
University of Michigan
September 2019 – April 2021 Spring 2018, AY 2019-20, AY 2020-21

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.

Fall 2020 Slides

 
 
 
 
 
Summer Program in Quantitative Methods of Social Research, ICPSR
Multilevel Models I: Introduction and Application
Summer Program in Quantitative Methods of Social Research, ICPSR
June 2018 – July 2019 Summer 2018, Summer 2019

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.

 
 
 
 
 
Summer Program in Quantitative Methods of Social Research, ICPSR
Introduction to the R Statistical Computing Environment
Summer Program in Quantitative Methods of Social Research, ICPSR
June 2018 – July 2019 Summer 2018, Summer 2019

Teaching Assistant

Two-week lecture series on graphics, data management, modeling, etc., in R. Held daily office hours.

Course Instructor: John Fox, Ph.D.

 
 
 
 
 
University of Michigan
STATS 415: Data Mining
University of Michigan
January 2018 – April 2018 Winter 2018

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.

 
 
 
 
 
University of Michigan
STATS 500: Statistical Learning I: Regression
University of Michigan
September 2017 – December 2017 Fall 2017

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.

 
 
 
 
 
University of Notre Dame
BIOS 40411: Biostatistics
University of Notre Dame
September 2017 – December 2017 Fall 2017

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.