Prerequisites: 

Must have completed an introductory graduate level statistics course covering material through OLS and logistic regression.

Description: 

Sampling is an applied statistics methods course that is focused on the design of the data collection. The course will concentrate on problems of applying sampling methods to human populations and will cover the main techniques used in sampling practice: simple random sampling, stratification, systematic selection, cluster sampling, multistage sampling, and probability proportional to size sampling. The course will also cover sampling frames, cost models, and sampling error estimation techniques.