Teaching
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Data Science Bootcamp
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Useful Links for Graduate Students
Spring 2021 Methods Reading Group Github Page
Missing Data Lecture Slides
Monte Carlo Methods Lecture Slides
Everything You Need to Know About the Linear Model Slides
Justin Grimmer's Read More
Harvard University, GOV 52: Models
Semester: Spring
Year offered: 2021
Link: Harvard Canvas Site
2021 Methods Reading Group
Semester: Spring
Year offered: 2021
American University: Statistics 618/GOV 618 (Every FALL): Bayesian Statistics for Social and Biomedical Sciences
Semester: Fall
Year offered: 2023
Course Description:
Principles and applications of modern statistical decision theory, with a special focus on Bayesian modeling, data analysis, inference, and optimal decision making. Prior and posterior; comparison of Bayesian and frequentist approaches, including minimax decision making and elementary game theory. Bayesian estimation,
Summer 2020 Joint Methods Seminars
Semester: Summer
Year offered: 2020
American University
Jeff Gill - "Critical Differences in Bayesian and Non-Bayesian Inference and Why the Former is Better"
University of North Carolina, Chapel Hill
Santiago Olivella - "An Introduction to Tree
Introduction to Survey Research
Semester: Spring
Year offered: 2020
This is an introduction to survey research and polling. Surveys, generally speaking, address questions that are of interest to political researchers, political actors, corporations, government, and journalists. The scientific principles that underlie survey work come from theoretical and empirical knowledge produced by
Survival Models
Year offered: 2019
Survival models for the social and biomedical sciences. An occasional course.
Harvard University: Government 61, Research Practice in Quantitative Methods
Semester: Spring
Year offered: 2018
Course Description
This class introduces students to a variety of statistical methods used to investigate political phenomena. We will address the principles behind these methods, their application, and their limitations. The course will be useful to those undertaking a quantitative methods thesis in
Harvard University: Government 2003, Bayesian Hierarchical Models
Semester: Spring
Year offered: 2018
Course Description:
This course covers Bayesian statistical model development with explicitly defined hierarchies. Such multilevel specifications allow researchers to account for different structures in the data and provide for the modeling of variation between defined groups. The course begins with simple nested linear