Abstract
A survey consists of a number of design steps. They are: definition of research goals, frame construction, choice of data collection mode, questionnaire development, sample design, data collection, and data processing. All design steps are interdependent and several iterations of the seven steps are usually necessary. A review of sampling methods is provided including simple random, systematic, stratified, unequal probability, and multistage sampling. An example of a combination of sampling methods, a master sample design, is given to show that it usually takes some engineering to produce a good sample design. To each sampling design there is at least one estimator that is a function of the sample data. The generalized regression estimator and the Horvitz–Thompson estimator are mentioned. It is important to consider the total survey error, not just the sampling error. Various methods for dealing with nonsampling errors are discussed in the bibliography provided.
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