Analysis of Complex Survey Data

Summer 2020


Prerequisites: The prerequisites for SURV702 include one or more graduate courses in statistics covering techniques through OLS and logistic regression, a course in applied sampling methods (e.g.SURV625), or permission of the instructor. The course is presented at a moderately advanced statistical level. Although the course will review the fundamentals of statistical analysis methods for survey data and provide detailed examples on the use of statistical software, it will be assumed that the students are familiar with statistical methods, including multiple regression and logistic regression. The initial lectures in the course syllabus will review the various complex features of sample designs and how they influence 2 estimation and inference based on survey data. The course syllabus and level of instruction also assume that students are familiar with basic sampling procedures, including simple random sampling, stratification, cluster sampling and multi-stage sample designs. Students who do not have graduate - level training in sampling techniques should expect to devote additional time during the first weeks of the course to supplemental readings on this topic.