Political Science by the Numbers
GOVT 367
Spring 2020 not offered

Crosslisting:
QAC 302 
Certificates: Applied Data Science 
Course Cluster: Data Analysis Minor 
This course covers the basics of probability theory and statistics. The main purpose of this course is to promote the understanding of statistical concepts and how these concepts can be used to make inferences about the political world. Topics include probability distributions, correlation analysis, linear regression, generalized linear models, maximum likelihood, logistic regression, causal inference, experiments, and nonparametric modeling. Lectures will mainly cover theory, while readings will connect the concepts described during lecture to problems in political science. Whenever possible, the instructor will draw upon research in political science to illustrate the why and how of a given concept or technique. Demonstrations will allow students to "play around" with abstract statistical concepts. Most lectures will have an interactive component involving class participation. Problem sets will cover some of the more technical aspects of what we discuss in class along with applications using real data. 
Credit: 1 
Gen Ed Area Dept:
SBS GOVT 
Course Format: Lecture  Grading Mode: Graded 
Level: UGRD 
Prerequisites: None 

Fulfills a Major Requirement for: (CADS)(DATAMN)(GOVT)(GOVTAmerican)(GOVTComparativ)(GOVTIntl.) 
Major Readings:
Sean Gailmard, STATISTICAL MODELING AND INFERENCE FOR SOCIAL SCIENCE. Cambridge, UK: Cambridge University Press. ISBN: 9781107003149

Examination and Assignments: One problem set per week, one collaborative research project, and one final 

