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Course List

PSCI 506 Advanced Topics in Methods

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  • Spring 2020
    Kevin A. Clarke, Curtis S. Signorino
    Spring 2020 — MW 10:30 - 12:00

    This course is designed for graduate students intending to pursue political methodology as a major field. It covers advanced statistical methods that are not yet standard fare in political methodology courses: e.g., semiparametric methods, nonparametric regression, time-series econometrics, Bayesian methods, and ideal point estimation. Course content will vary year to year, and this semester will focus more heavily on Bayesian methods, simulation-based estimation, and ideal point estimation. As a research workshop, this course also allows students to pursue areas of individual interest in more depth, and therefore course content is determined based on the interests of both the professor and the students. Prerequisites: PSC 404, PSC 405, and PSC 505.

  • Spring 2017
    Curtis S. Signorino
    Spring 2017 — T 9:30 - 12:00
    Course Syllabus

    This course covers advanced statistical methods that go beyond linear models and maximum likelihood estimation. Course content will vary year to year and will be determined by the interests of the students and the instructor. Typical topics will include Bayesian markov chain monte carlo methods, ideal point estimation, non-parametric and semi-parametric estimation, causal inference, and machine learning techniques. As a research workshop, this course also allows students to pursue areas of individual interest in more depth. Students are assumed to have taken graduate courses in mathematical probability and inference (PSC 404), linear models (PSC 405), and maximum likelihood estimation (PSC 505). Students will be expected to know how to program their own estimators in R.

  • Spring 2015
    Curtis S. Signorino
    Spring 2015 — R 14:00 - 16:40
    Course Syllabus

    This course covers advanced statistical methods that go beyond linear models and maximum likelihood estimation. Course content will vary year to year and will be determined by the interests of the students and the instructor. Typical topics will include Bayesian markov chain monte carlo methods, ideal point estimation, non-parametric and semi-parametric estimation, causal inference, and machine learning techniques. As a research workshop, this course also allows students to pursue areas of individual interest in more depth. Students are assumed to have taken graduate courses in mathematical probability and inference (PSC 404), linear models (PSC 405), and maximum likelihood estimation (PSC 505). Students will be expected to know how to program their own estimators in R.

  • Spring 2014
    Kevin A. Clarke
    Spring 2014 — T 14:00 - 16:40
    Course Syllabus

    This course is designed for graduate students intending to pursue political methodology as a major field. It covers advanced statistical methods that are not yet standard fare in political methodology courses: e.g., semiparametric methods, nonparametric regression, time-series econometrics, Bayesian methods, and ideal point estimation. Course content will vary year to year, and this semester will focus more heavily on Bayesian methods, simulation-based estimation, and ideal point estimation. As a research workshop, this course also allows students to pursue areas of individual interest in more depth, and therefore course content is determined based on the interests of both the professor and the students. Prerequisites: PSC 404, PSC 405, and PSC 505.

  • Spring 2012
    Kevin A. Clarke
    Spring 2012 — R 15:25 - 18:05

    This course is designed for graduate students intending to pursue political methodology as a major field. It covers advanced statistical methods that are not yet standard fare in political methodology courses: e.g., semiparametric methods, nonparametric regression, time-series econometrics, Bayesian methods, and ideal point estimation. Course content will vary year to year, and this semester will focus more heavily on Bayesian methods, simulation-based estimation, and ideal point estimation. As a research workshop, this course also allows students to pursue areas of individual interest in more depth, and therefore course content is determined based on the interests of both the professor and the students. Prerequisites: PSC 404, PSC 405, and PSC 505.

  • Spring 2010
    Kevin A. Clarke
    Spring 2010 — W 14:00 - 16:40
    Course Website
    Course Syllabus

    This course is designed for graduate students intending to pursue political methodology as a major field. It covers advanced statistical methods that are not yet standard fare in political methodology courses: e.g., semiparametric methods, nonparametric regression, time-series econometrics, Bayesian methods, and ideal point estimation. Course content will vary year to year, and this semester will focus more heavily on Bayesian methods, simulation-based estimation, and ideal point estimation. As a research workshop, this course also allows students to pursue areas of individual interest in more depth, and therefore course content is determined based on the interests of both the professor and the students. Prerequisites: PSC 404, PSC 405, and PSC 505.

  • Spring 2007

    This course is designed for graduate students intending to pursue political methodology as a major field. It covers advanced statistical methods that are not yet standard fare in political methodology courses: e.g., semiparametric methods, nonparametric regression, time-series econometrics, Bayesian methods, and ideal point estimation. Course content will vary year to year, and this semester will focus more heavily on Bayesian methods, simulation-based estimation, and ideal point estimation. As a research workshop, this course also allows students to pursue areas of individual interest in more depth, and therefore course content is determined based on the interests of both the professor and the students. Prerequisites: PSC 404, PSC 405, and PSC 505.