Introduction to Survey Sampling and Estimation
STAT 160
Subject & Catalog Number
Course Information
Description
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 weights, and survey-weighted analysis. The course also introduces contemporary topics including nonprobability samples, data integration, capture-recapture, small-area estimation, and analysis of public-use survey data, with computational examples in R.
Recommended Prep
Stat 110, Stat 111 (may be taken concurrently); Math 21A or equivalent, Math 21B or equivalent; basics of R programming
Available for Harvard Cross Registration
NOTE: This course requires additional sections; you will be prompted to choose secondary components during the Add to Cart process
