Applied Sampling

Spring 2019



Completion of either Social Statistics I (SURV 601) or Statistical Methods I (SURV 615), or a graduate course in statistics approved by the instructor.


Applied Sampling is an applied statistical methods course, but differs from most statistical methods courses. It is concerned almost exclusively with the design of data collection. The course examines problems of applying sampling methods to human populations, particularly the principles of sample selection and basic estimation. The course is at a moderately advanced statistical level, and while not developing the mathematical aspects of sampling theory, statistical notation and outlines of algebraic proofs will be given. The course 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. These methods will be elaborated in two types of sample designs, area probability and telephone sampling. The course will also cover sampling frames, cost models, sampling error estimation techniques, non-sampling errors, and compensating for missing data.