PSCI 505 Quantitative Methods 3
- Fall 2024
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 2023
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 2022
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 2020
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 2019Curtis S. SignorinoFall 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 2018Curtis S. SignorinoFall 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
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
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
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
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
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
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
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
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.