TEACHING

Advanced Statistics

SPI600C

I was the instructor for this course over the summer of 2021. This course is part of the Public and International Affairs Junior Summer Institute (PPIA JSI) from the School of Public and International Affairs at Princeton University. PPIA JSI is an intensive seven-week program for college students that want to pursue graduate level training in public policy. This intensive course provides an overview of probability theory, hypothesis testing, and causal inference including difference in difference, the linear regression model, sharp regression discontinuity, and instrumental variables models. You can find my syllabus here.

Applied Quantitative Analysis
POL 346

I was the head assistant instructor for this course over Spring 2021. This course is taught by Professor Omar Wasow. This course focuses on developing an intuition for statistics and applying it through data analysis, regression models and a final project. We wrestle with what makes a good research question, play with data to see how statistical methods can help us make sense of real world concerns, and work at communicating quantitative findings clearly to broad audiences. Particular attention is paid to applying these techniques in Junior Papers and Senior Theses. Coursework involves using the R statistical platform.


Gen Z Voting Challenge
POL 426

I was an assistant instructor for this course over Fall 2020. This was a Princeton Challenge course taught by Professor Tali Mendelberg. Students designed and implemented efforts to register young Americans for the 2020 presidential election. The class partnered with a Trenton charter school, STEMCivics. The class read relevant scholarship to design an intervention focused on social media and peer-to-peer connections. The class also worked with STEMCivics students on developing and writing a letter to their Congressperson. The collective letters were sent to Congressperson Bonnie Watson-Coleman, and Rep. Bonnie Watson-Coleman met virtually with the students to discuss their concerns. I predominately assisted the class with research design, statistics, and logistics.

Introduction to Quantitative Social Science
POL 345

I was an assistant instructor for this course over Fall 2020. This is an introductory statistics course in the Politics Department at Princeton. It was taught by Professor Marc Ratkovic. This course provides an introduction to causal inference, probability theory, and estimation. The focus of this course was on hands-on data analysis and the practical application of basic statistical methods to real-world, relevant problems. The class used R for statistical analyses.

Principles of Microeconomics
ECON 111

I was a prefect for this course during the Spring 2013 and Fall 2014 trimesters for Professor Faress Bhuiyan at Carleton College. This course provides the foundational principles for studying microeconomics. Topics covered in the course include consumer choice theory; the formation of prices under competition, monopoly, and other market structures; the determination of wages, profits, and income from capital; the distribution of income; and an analysis of policy directed towards problems of public finance, pollution, natural resources, and public goods.

Advanced Statistics
WWS600C

I was an assistant instructor for this course over the summer of 2020. This course is part of the Public and International Affairs Junior Summer Institute (PPIA JSI) from the School of Public and International Affairs at Princeton University. PPIA JSI is an intensive seven-week program for college students that want to pursue graduate level training in public policy. This intensive course provides an overview of probability theory, hypothesis testing, and causal inference including difference in difference, the linear regression model, sharp regression discontinuity, and instrumental variables models. You can find my materials for precept sessions going over course content in R here.

Introduction to Statistics
WWS600B

I was an assistant instructor for this course over the summer of 2020. This course is part of the Public and International Affairs Junior Summer Institute (PPIA JSI) from the School of Public and International Affairs at Princeton University. PPIA JSI is an intensive seven-week program for college students that want to pursue graduate level training in public policy. The purpose of this course is to introduce students to the basic empirical methods used for the analysis of public policy. The main topics covered over the course included: descriptive statistics, probability theory, hypothesis testing, and simple and multiple regression. You can find my materials for precept sessions going over course content in R here.