Pippa Norris Photo

Pippa Norris

Paul F. McGuire Lecturer in Comparative Politics
Office Address
79 John F. Kennedy St. Littauer Bldg 110

This course aims to sharpen your understanding of public opinion and develop practical skills in applied survey research.  Each week is divided into two sessions. Monday classes provide the theoretical framework for understanding public opinion including the nature of mass beliefs, policy attitudes, political participation, value change, elections and parties, voting behavior, social cleavages and partisan orientations, knowledge and beliefs, the media and campaigns, and the nature of public opinion. It covers these issues by comparing the United States with other major comparable postindustrial societies as well as across a broader range of developing societies around the world.

Wednesday classes deepen applied skills in using survey research to understand these topics. We will work hands-on from web-based online applications and shared datasets, for example, the American National Election Survey, the U.S. General Social Survey, the Eurobarometer, the European Social Survey, the Afro-barometer, the World Values Survey, the International Social Survey Program, and national equivalents. The course will use a broadly comparative approach using evidence from a wide range of data sources and countries. Students acquire the applied skills to use these resources for research projects. The applied classes cover soup-to-nuts issues of valid and reliable research design; sampling and fieldwork; theory construction, model building, and hypothesis-testing; survey data sources; the appropriate statistical techniques for analyzing survey data; and the professional presentation of findings and graphical results.

The course is designed for careers analyzing public opinion polling and survey research, policy analysis, campaign management, broadcasting and journalism, and statistics.

There are no prerequisites for taking the class but basic familiarity with statistical programs such as Stata and SPSS would be advantageous.