University at Buffalo 3 credits Political Science
Presents an overview of the likelihood theory of statistical inference and its wide range of uses in applied quantitative political science. More specifically, discusses more advanced forms of regression models estimated using maximum likelihood, how to estimate these models, and how to make inferences from them in applied settings. Topics can include, but are not limited to, binary, ordinal, and multinomial logit/probit models; count models; and duration models. Presupposes basic to moderate familiarity with a statistical software package. Prerequisites: PSC 500, 508, and 531, or equivalents with permission of instructor.
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