Objective 1: The course introduces students to advanced statistical techniques for the analysis of quantitative data, in particular time series analysis and multilevel modeling.
Objective 2: Students acquire practical data analysis skills by applying and using these techniques with quantitative data of their own choice.
Content: The aim of this course is to introduce students to advanced statistical techniques for the analysis of quantitative data that are frequently used in the literature of political science and public administration. The focus is specifically on explaining dynamic changes over time and how to account for contextual, macro-level effects on micro-level relationships. The techniques covered are aggregate and cross-sectional time series analysis and event history analysis as well as multilevel models.
Methods of instruction
Lectures, discussion, and assignments.
Box-Steffensmeier, Janet M., John R. Freeman, Matthew P. Hitt, and Jon C. W. Pevehouse. 2014. Time Series Analysis for the Social Sciences. New York: Cambridge University Press.
Luke, Douglas A. 2004. Multilevel Modeling. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-143. Thousand Oaks, CA: Sage.
Box-Steffensmeier, Janet M., Henry E. Brady, and David Collier. 2008. The Oxford Handbook of Political Methodology. Oxford: Oxford University Press.
(3 chapters required)
Field, Andy, Jeremy Miles, and Zoë Field. 2012. Discovering Statistics Using R. London: Sage.
(1 chapter required)
Additional readings (listed in syllabus on Blackboard).
Assignments, research paper, and class participation.
See Preliminary Info