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Course List

PSCI 505 Maximum Likelihood Estimation

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  • Fall 2020
    Curtis S. Signorino
    Fall 2020 — MW 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2019
    Curtis S. Signorino
    Fall 2019 — MW 10:30 - 12:00

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2018
    Curtis S. Signorino
    Fall 2018 — MW 10:30 - 12:00

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2017
    Curtis S. Signorino
    Fall 2017 — TR 8:45 - 10:30
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2016

    W 1000-1130 & F 0900-1015. The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2015
    Curtis S. Signorino
    Fall 2015 — MW 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2014
    Curtis S. Signorino
    Fall 2014 — TR 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2013
    Curtis S. Signorino
    Fall 2013 — TR 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2012
    Curtis S. Signorino
    Fall 2012 — TR 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2011
    Curtis S. Signorino
    Fall 2011 — TR 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2010
    Curtis S. Signorino
    Fall 2010 — TR 10:30 - 12:00
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.

  • Fall 2009
    Curtis S. Signorino
    Fall 2009 — R 12:30 - 15:15
    Course Syllabus

    The classical linear regression model is inappropriate for many of the most interesting problems in political science. This course builds upon the analytical foundations of PSC 404 and 405, taking the latter's emphasis on the classical linear model as its point of departure. Here students will learn methods to analyze models and data for event counts, durations, censoring, truncation, selection, multinomial ordered/unordered categories, strategic choices, spatial voting models, and time series. A major goal of the course will be to teach students how to develop new models and techniques for analyzing issues they encounter in their own research.