Courses on Methodology

Michigan State University, Assistant Professor, Fall 2017- present

  1. Multilevel Models, graduate level, Spring 2018, Spring 2021
  2. Quantitative Techniques in Political Science, graduate level, Fall 2017, Fall 2018, Fall 2019, Fall 2020
    • Lab 1: Introduction to R & Reproducible Research
    • Lab 2: Reading and Visualizing Data
    • Lab 3: Vectors and Matrices
    • Lab 4: Solving Linear Systems of Equations
    • Lab 5: Functions, If Statements, and For Loops
    • Lab 6: Representing Numbers in the Computer
    • Lab 7: Multivariate Calculus & Optimization Problems
    • Lab 8: Probability. Die and Decks of Cards. Card Games!
    • Lab 9: Random Variables and Probability Distributions
    • Lab 10: Descriptive Statistics & Visualization
    • Lab 11: Hypothesis Testing
    • Extra (in class): Integrals; Law of Large Numbers and Central Limit Theorem
  3. Quantitative Techniques in Political Science II, graduate level (Linear Regression), Spring 2019, Spring 2020, Spring 2021
    • R Labs:
    • Lab 1: Causality and Measurment
    • Lab 2: The Basics of Linear Regression
    • Lab 3: Diagnostics
    • Lab 4: Visualization & Prediction
    • Lab 5: Unusual Data
    • Lab 6: Interactions
    • Lab 7: Missing Data
  4. Generalized Linear Models, graduate level, Fall 2018,
    • Lab 1: The Likelihood Model of Inference
    • Lab 2: Binomial Models, Predicted Probabilites, and First Differences
    • Lab 3: Calculation of Predicted Probabilities Using the Observed Value Approach
    • Lab 4: Models for Count Outcomes: Poisson, Negative-Binomial, and Zero-inflated Models. Simulation of Predictions.
    • Lab 5: Models for Unordered Categorical Dependent Variables. Simulation of Predictions.
    • Lab 6: Models for Ordered Categorical Dependent Variables. Simulation of Predictions.
    • Lab 7: Bootstrapping, Model Checking, Sensitivity Analysis, Cross-validation
    • Lab 8: Missing Data

University of Virginia, Lecturer, Fall 2016- Spring 2017

  1. Multilevel Models, graduate level, Spring 2017
    • Bayesian and Frequentist Multilevel Models
    • Syllabus
  2. Generalized Linear Models, graduate level, Fall 2016
  3. Mathematics for Political Science, graduate level, Fall 2016
    • One credit course, mandatory for first year students
    • Syllabus

Washington University in Saint Louis, Teaching Assistant

  1. Multilevel Modeling for Quantitative Research, graduate level
  2. Measurement and Latent Trait Models, graduate level
    • Professor: Jacob Montgomery
  3. Quantitative Political Methodology, undergraduate level

Programming Workshops

  1. An Introduction to R, University of Virginia, 2016
  2. Handling Non-English Text in Python, Methods Workshop, WUStL, 2014
  3. Web Mining with Python, WUStL, 2014
  4. An Introduction to Python, WUStL, 2012

Courses on Institutions and Behavior, undergraduate level

Washington University in Saint Louis, Teaching Assistant

  1. Politics of a Connected Public
  2. Latin American Politics Through Film
    • Professor: Brian F. Crisp
  3. Presidents, Legislators, and Economic Policy in Latin America
    • Professor: Brian F. Crisp