Survey Sample Methods AY 2020

The module aims at introducing a set of principles of survey design that are the basis of standard practices in the field. It presents statistical concepts and techniques in sample design, execution, and estimation, and models of behavior describing errors in responding to survey questions.

•Introduction to survey methodology: need for survey sampling, terminology, notation, estimation strategy, survey errors, probability sampling and non-probability sampling;

•Inference and error in surveys;  

•Target populations, sampling frames and coverage error;  

•Sampling techniques: simple random sampling, systematic sampling, stratified sampling, cluster sampling, multi-stage sampling, unequal probability sampling;

•Basic inference for survey data: bias of estimators, inclusion probabilities, standard errors, finite population correction, variance estimation, confidence intervals, proportions, domains, ratio estimation, Horvitz-Thompson estimator, design-based inference,

•Specific topics in survey sampling: double sampling procedures, randomized response models, small area estimation, resampling methods,

•Analysis of survey data and illustration with statistical software.

At the end of the module, the students should be able: