QUANT METH 4 TOPICS IN METHODS, 4 pts, GU4726
QUANT METH 4 TOPICS IN ME
This course is the fourth course in the graduate-level sequence on quantitative political methodology oﬀered in the Department of Political Science. Students will learn a variety of ad-vanced topics in political methodology, such as machine learning, recent measurement methods (e.g., ideal point estimation, text analysis, list experiment, and conjoint experiment), network analysis, and causal inference with spatial and network data. Students will collaborate to present discussion papers throughout the semester. The main goal of this course is to help students to write a ﬁnal paper that applies or develops advanced statistical methods. This course builds on the materials covered in POLS 4700, 4720, 4722, and 4724, or their equivalent courses (i.e., probability, statistics, linear regression, logistic regression, causal inference with observational and experimental data, and knowledge of statistical computing environment R).
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- Day, Time & Location
- MW 2:40PM-3:55PM To be announced
- Naoki Egami