Columbia’s M.S. in Quantitative Methods in the Social Sciences bridges sociology, economics, political science, and psychology through analytics. These project ideas combine policy evaluation, behavioral modeling, and survey research using modern quantitative methods.
Analyzing the Effects of Minimum Wage on Employment Using Panel Data
Predicting Voter Turnout Using Demographic and Psychographic Features
Social Media Sentiment Analysis of Climate Change Movements
Structural Equation Modeling of Student Performance Predictors
Forecasting Urban Crime Using Multivariate Time Series Models
Public Health Intervention Impact Using Difference-in-Differences
Causal Inference in Gender Bias Within Hiring Processes
Survey Weighting and Nonresponse Bias Adjustment in Political Polling
Predicting Education Outcomes with Machine Learning on Census Data
Policy Evaluation: Universal Basic Income and Labor Market Response
Quantifying Trust in Government Using Longitudinal Survey Data
Sentiment Trends in Legislative Bills Using NLP Models
Spatial Analysis of Social Services Accessibility in Urban Areas
Impact of Gig Economy on Income Stability Using Cross-Sectional Data
Regression Discontinuity Design in Educational Reform Studies
Predicting Mental Health Risk from Socioeconomic Indicators
Social Network Analysis of Political Polarization on Twitter
Multilevel Modeling for Neighborhood Effects on Child Wellbeing
Data Visualization Dashboard for Civic Engagement Trends
Predictive Analytics for Voter Issue Prioritization in Swing States
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