JEFF GILL

Distinguished Professor, Department of Government
Department of Mathematics & Statistics,
Founding Director, Center for Data Science
Member, Center for Neuroscience and Behavior

American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016

Teaching

  • Harvard University, GOV 52: Models

    Semester: Spring

    Year offered: 2021

    Link: Harvard Canvas Site

  • 2021 Methods Reading Group

    Semester: Spring

    Year offered: 2021

    Github Page

  • American University: Statistics 618/GOV 618 (Every FALL): Bayesian Statistics for Social and Biomedical Sciences

    Semester: Fall

    Year offered: 2021

    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

  • Teaching Datasets

    hpd.gamma function in R

    state.short.dat dataset

    pbm.pim2.dat dataset

    Multivariate normal code

    North Carolina dataset

    Trauma dataset

    Indomethacin dataset

    Dogs dataset