Description: Laboratory, three hours. Requisites: courses 200A, 200B. Corequisite: course 200C. Study of theory and application of linear regression analysis in political and social sciences. Starting with basic knowledge of probability theory and statistics, investigation of computation and interpretation of regression results, their statistical justifications, diagnostics for violations of assumptions, stability of results under perturbations of data and models, and extensions into nonstandard situations. Topics may include classical linear model, statistical inference and hypothesis testing, vector geometry of regression, diagnostics, weighted least squares, cross validation and model selection, resampling, outliers, missing data, errors in variables, transformations, robust regression, logistic regression, and modern computing packages. Letter grading.

Units: 4.0