Please note: This course will be taught online only. In person study is not available for this course.
Yanna Krupnikov integrates psychology and political science in order to identify points at which new information can have the most profound effect on the way people form political opinions, make political choices, and, ultimately, take political actions. Some of her research, which has been recently published in a book, argues that political independents really aren’t independent but are ashamed of both parties and so choose to claim independence rather than associate with Republicans or Democrats.
This course will focus on advanced topics in survey design and analysis. Topics covered include different approaches to sampling, the effects of survey mode, and tools for analysing and enriching survey data, including question-wording, measurement and treatment validity, measurement of reported behaviour as well as social network studies. The course will also focus on designing and analysing survey experiments and current debates about the use of varying samples in these experiments. In addition, the course will consider various types of available samples, and the trade-offs in using certain sample types.
Participants will gain an advanced understanding of best practices for analysing survey data and designing and analysing various types of survey experiments. Participants will also gain hands-on experience in analysing survey data and constructing and analysing survey experiments. Participants can also pose questions about their own ongoing survey research and data projects.
Course participants who want to take part in the hands-on analysis components of the course should have some familiarity with Stata or R. Participants who want to take part in the analysis components should also be comfortable with descriptive statistics and should have at least some familiarity with OLS regression. No additional background readings are required for this course.
Background knowledge required
OLS = moderate
Stata = elementary OR
R = elementary
Linear Regression = elementary