8 - The Study Population: Sampling

Abstract

This chapter provides an overview on sampling. The first step in a discussion of sampling is the identification of the target population or universe from which a sample is to be drawn. A population is the totality of all the cases, called population elements, or units, that meet some designated set of specifications. When one population is included in another, the former is called a subpopulation or a stratum. It is essential that the population units be clearly definable. Identifying the population properly is a difficult problem in itself. In any study, the choice of sample determines the generalizability of the results. To be useful, a sample must satisfy three criteria: (1) the sample must represent the population, (2) the sampling procedure must be efficient and economical, and (3) the estimates of population characteristics obtained from the sample must be precise and testable for reliability. The basic distinction in sampling is between probability and nonprobability samples. A probability sample is one in which the probability that any element of the population is included can be specified; in the simplest case, each element is equiprobable, but this is not necessary. It is only necessary that the probability of inclusion be knowable. In contrast, the probability of any element's inclusion in a nonprobability sample is unknown. The chapter also discusses the advantages and disadvantages of sampling.