Teaching

Instructional/Teaching Assistantships

I grade, lead study sessions, proctor exams and lecture as needed for a variety of courses in the Department of Statistics & Operations Research at UNC and the Wake Forest School of Medicine.

See course history below.

Statistical Modeling (THSS 732): Spring 2024
An introduction to the application of common types of generalized linear models. Additional topics include methods for analyzing longitudinal data including ANCOVA, mixed effects models, and survival analysis. Special topics cover methods for handling missing data and common statistical machine learning algorithms.
Introduction to Biostatistics (THSS 730): Fall 2023
An introduction to statistical concepts and basic methodologies that are prevalent in biomedical literature. It includes discussion of descriptive statistics, probability, sampling distributions, hypothesis testing, simple linear regression, correlation, one-way analysis of variance, categorical data analysis, logistic regression, survival analysis, and nonparametric methods.

Machine Learning (STOR 565): Spring 2022 & Fall 2020
Introduction to the theory and methods of machine learning including classification; Bayes risk/rule, linear discriminant analysis, logistic regression, nearest neighbors, and support vector machines; clustering algorithms; overfitting, estimation error, cross validation.
Gave special topic lecture on tidymodels (2022/03/29): tidymodels
Methods of Data Analysis (STOR 455): Fall 2021
Review of basic inference; two-sample comparisons; correlation; introduction to matrices; simple and multiple regression (including significance tests, diagnostics, variable selection); analysis of variance; use of statistical software.
Intro to Data Models & Inference (STOR 155): Spring & Summer 2021, Spring & Fall 2023, Spring 2024
Data analysis; correlation and regression; sampling and experimental design; basic probability (random variables, expected values, normal and binomial distributions); hypothesis testing and confidence intervals for means, proportions, and regression parameters; use of spreadsheet software.
Gave lecture on Bernoulli trials and derivative distributions (2024/03/27)

Introduction to Regression & Data Science (STA 112): Fall 2019 & Spring 2020
A foundational course in regression and data science. The course introduces data analysis through statistical computing in R, least-squares and logistic regression, model selection, and data visualization.
Elementary Probability & Statistics (STA 111): Spring 2019 & Summer 2019
Data collection and visualization, exploratory analysis, introductory probability, inference techniques for one variable, and statistical literacy.
Calculus with Analytic Geometry (MATH 111): Fall 2018
Functions of a real variable, trigonometric, exponential and logarithmic functions, limits, continuity, differentiation, applications of derivatives, indeterminate forms, introduction to integration, the fundamental theorem of calculus.

Experimental Design, Analysis & Presentation (BIO 134): Fall 2017
An introduction into process and methodology in biological sciences, including fundamental concepts of biological research. The course includes 1) information techniques and critical evaluation of primary literature in biology; 2) scientific writing including ethics and presentation; and 3) experimental design and statistical analysis with R.