This course covers selected topics in research design and applied statistics offering students a workshop where they will develop and present quantitative empirical projects. The course will provide an overview of current best practices for the design, implementation, analysis, and presentation of empirical work with a particular emphasis on ways to enhance the transparency, reproducibility, and credibility of such work.
We meet every two weeks over the spring and fall semesters. During the fall semester, we will examine strategies for causal inference in experimental and observational designs. During the spring semester we will cover specific topics tailored to the research projects of the students in the course. The topics outlined below are provided as possible examples, but are subject to change based on student input during the fall. The course is structured around 1) lectures that provide a broad overview of the concepts and theories of a given method, 2) applications that explore the practice (and pitfalls) of given method in recent published work and 3) presentations in which students present and comment on their on-going projects.
Download a recent syllabus.