Teaching Assistant at Duke
STA 221: Regression Analysis: Theory and Application
Head TA (Fall 2024, Spring 2025)
Directed and managed a team of 4 (Fall 2024)/ 5 (Spring 2025) Teaching Assistants to ensure consistent instruction and grading across all course sections for over 35 (Fall 2024)/ 60 (Spring 2025) students.
Collaborated directly with the lecturer to design, refine, and edit course materials, including challenging homework and lab problems focusing on regression theory and application.
Developed a comprehensive computational review lab to serve as a persistent, reproducible coding reference for all students.
Delivered a high-stakes guest lecture on Logistic Regression, demonstrating advanced command of course material.
Student Feedback: “Kat is very knowledgeable and knew how to explain questions in a way we could easily understand. She made sure to be patient and encouraged us to understand the process by applying it instead of just memorizing.”
STA 101: Data Analysis and Statistical Inference
Head TA (Spring 2024)
Coordinated a TA team of 8 members for a high-enrollment introductory course.
Led weekly computational lab sessions and dedicated office hours, translating complex statistical concepts into easily digestible terms.
Delivered two guest lectures covering core statistical lessons for the entire student body.
Student Feedback: “She knows her stuff. Was really helpful and was always checking in with us. Explained stuff in ways we could understand. Everything seemed common sense when she explained.”
STA 470: Introduction to Statistical Consulting
Fall 2023
Mentored and advised students on integrating statistical methods into real-world projects for external clients.
Provided critical, constructive feedback focused on the effective communication of complex statistical findings and data visualizations to non-technical audiences.
STA 199: Introduction to Data Science and Statistical Thinking
Provided hands-on assistance to students during labs and office hours, focusing on foundational Data Science principles and R programming.
Evaluated student projects and provided detailed guidance on structuring reproducible reporting (using tools like R Markdown/Quarto).
Student Feedback: “Kat was great about explaining necessary material that we may not have seen in class while also allowing us to work through problems as a group and not solving problems for us.”
