(PL SC 519)
Survey Methods II: Analysis of Survey Data (3) Intermediate course on the statistical analysis of survey data: topics include weighting, complex surveys, missing data, and contextual analysis.
SOC (PL SC) 519 Survey Methods II: Analysis of Survey Data (3)
This is an intermediate level course in quantitative analysis. It is intended for graduate students who have completed 1-2 semesters of graduate-level statistics (not general research methods) and who are interested in the application of social statistics to the unique aspects of data collected by way of surveys. Surveys have a combination of qualities that represent challenges to valid inference. These include cluster and stratified sampling, under-representation of some groups due to differential response rates, missing data due to item non-response, cross-sectional design, and coarse measurement. Quite often we use surveys to test theories that the original survey designer did not intend to address, raising issues of validity and reliability of measurement. At the same time, surveys offer a number of opportunities and, when combined with other surveys (pooled cross sections) or merged with contextual data, can address a wide range of theoretical puzzles in the social sciences. This course provides an introduction to techniques in applied statistics that have developed specifically to address the special features of survey data. Examples of such techniques are: use of design weights, post-stratification weights, merging surveys with other surveys or auxiliary data, missing data imputation, challenges of causal inference. The class will blend an understanding of the core statistical issues with an emphasis on acquiring an intuition for the theory underlying the statistical models rather than focusing on proofs and estimation. This will provide a foundation for frequent hands-on applications in this seminar and for enrollment in more advanced or more in-depth courses offered by the Statistics department and the various social science departments.
Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.