The growing dominance of data and big data in shaping human and planetary decisions underscores the urgent need for statistical literacy and strong data analysis skills.nnBuilding on the 200-level Quantitative Research Methods course, this class deepens both theoretical understanding and applied competence in statistical analysis. Through key concepts of estimation and hypothesis testing, students will learn the foundations of modern data analysis and explore the underlying mechanics of regression models. The course trains students to diagnose and address real-world data challenges, conduct rigorous program and policy evaluations, and produce effective data visualizations using statistical software.nnKey topics include non-linear models, cross-sectional methods (Linear Probability, Logit, and Probit models), panel data techniques, instrumental variable estimation, and model diagnostics such as multicollinearity, heteroscedasticity, and specification tests.nnTogether with Quantitative and Qualitative Research Methods, this course provides a strong platform for students aspiring to careers in research, policy analysis, or development-oriented institutions, as well as for those pursuing graduate studies that require advanced analytical skills.
