Description: Seminar, three hours. Preparation: knowledge of calculus, basic probability, and statistics, including linear regression and experience with computing in R. Recommended requisite: course 200C. Focus on causal inference in social science settings, particularly where randomized experiments may be difficult or impossible to implement. Introduction to commonly used estimation techniques, with focus on conditions under which they produce causal estimates. Emphasis on understanding and maximizing credibility of causal claims researchers can make given pragmatic limitations. S/U or letter grading.
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