Technical Skills

Statistical Software: R and Stata (data management, recoding, and analysis)

Quantitative: OLS Regression Models, Multinomial Logit Models, Cumulative Logit Models, Multilevel & Panel Data Analysis, MAIHDA Approach, Survey Research (collection, management, and distribution), Qualtrics

Relevant Courses: Overview of Sociological Methods, Graduate Statistical Analysis I, Graduate Statistical Analysis II, Social Network Analysis, Multilevel & Panel Data Analysis

General Tools: Github, R Studio

Teaching Undergraduate Statistics

“Quantitative Methods in Sociology” (SOC 312): Instructor of Record (Summer 2023, Spring 2024, Spring 2025) in the Department of Sociology at the University of Oregon

Course Description: This course will teach the fundamentals of analyzing numerical data in a social science context. Students will learn effective ways of presenting informational summaries, the use of statistical inference from samples to populations, the linear model that forms the basis of much social science research, and the ability to think critically about how to consume statistical information. Emphasis will be on an intuitive understanding of statistical results, and on their practical application. This statistics course is structured into five major thematic modules: (1) understanding data, (2) the distribution of a variable, (3) measuring association, (4) statistical inferences) and (5) building OLS regression models. Along with fundamental concepts in statistics, students will learn how to code using R programming.