STAT 160
Introduction to Survey Sampling and Estimation
Introduces modern methods for survey sampling design and finite-population inference, with emphasis on probability sampling, design-based estimation, and the practical consequences of complex survey designs. Topics include simple random sampling, ratio and regression estimation, stratification and allocation, cluster and multistage sampling, systematic and PPS sampling, Horvitz-Thompson estimation, survey weights, nonresponse adjustment, calibration, raking, variance estimation, replicate…
Topics
- simple random sampling
- ratio and regression estimation
- stratification and allocation
- cluster and multistage sampling
- systematic and PPS sampling
- Horvitz-Thompson estimation
- survey weights
- nonresponse adjustment
- calibration
- raking
- variance estimation
- replicate…
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗Public 2026-2027 offerings