Applied Social Statistics
Core applied statistics sequence covering regression, inference, simulation, causal inference, prediction, and modern statistical workflow.
Current Courses
Course materials
Machine Learning for Policy Analysis
Graduate course on machine learning for policy analysis.
Visualizing Data
Freshman Scholars Institute course on visualizing data, with Brandon M. Stewart as course head.
Sociology Summer Methods Camp
Graduate methods camp for incoming Princeton Sociology students.
Previous Courses
Advanced Social Statistics
Advanced social statistics course with materials on modeling, inference, missing data, causal inference, regularization, and research design.
Machine Learning with Social Data
Courses on using machine learning for social data, with attention to prediction, measurement, interpretation, and social-science applications.
Text as Data
Statistical text analysis for the social sciences, emphasizing measurement, validation, topic models, supervised learning, and substantive interpretation.
Growing Up Poor Across America
Course materials for studying poverty, inequality, and social mobility across American contexts.
Sociology Statistics Reading Group
Presentations, readings, and discussion materials from the Sociology Statistics Reading Group.