Courses

PLSC 427: Political Opinion.  This is an upper division course with four student goals: (1) Gain a better understanding of what ordinary US citizens think about politics, what they think about the major issues and policy debates, and how they feel about the way the government actually works. (2) Gain a better understanding of the role that citizen opinions play in the give and take of politics.  Do the opinions of ordinary citizens make a difference? (3) Learn the different ways of studying public opinion.  What are the advantages and disadvantages of public opinion polls, drawing conclusions from election returns, focus groups, and internet traffic?  How can we think critically about news reports of public opinion? (4) Gain substantial hands-on experience in aspects of public opinion polling and analysis

PLSC/SOC 518: Survey Methodology I. This is a course for doctoral students in the social and behavioral sciences, focusing on the science of data collection using structured questionnaires.  We examine current best practices, including those concerning protection of human subjects, for the recruitment and retention of survey respondents.  Most of the course is devoted to questionnaire design, with special attention to the impact of research design decisions on data reliability and validity. Hands on applications and team projects are used throughout the semester.

PLSC/SOC 519: Survey Methodology II. This course is intended for doctoral students who have completed two semesters of applied statistics and wish to learn how to extend that knowledge to the proper application of these techniques for survey data sets that typically depart from simple random sampling.  The first half of the course focuses on analysis of data that  accounts for purposeful departures from random sampling (use of stratification, clustering, and over-sampling of small groups), and accounts for non-response bias (e.g., post-stratification weighting).  The second half includes specific techniques in the survey analyst’s “toolkit.”  These vary each semester and include topics such as multiple imputation of missing data, augmenting surveys with geo-coded data, measurement, and analysis of repeated surveys.