This chapter examines the ways that populations under study in social scientific research are understood, and how researchers select smaller numbers of members of the population, a “sample,” in order to conduct research. It explores the issue of sampling and its role in social scientific research. This chapter outlines the factors that researchers should consider when selecting a population for a study, beginning with the clear identification of the population to be studied. The second important factor is choosing an appropriate sample, which is influenced by the type of research being conducted, the knowledge you have about the population, the sample selection method, and the sample size. The sample selection method is further divided into two categories: probability sampling (based on probability theory) and non-probability sampling (not based on probability theory).
With regards to probability sampling, the chapter outlines the logic of drawing representative samples from larger populations using statistical analysis. The issues discussed include how to determine a sampling distribution, weigh possible sampling errors, and use different types of probability sampling (i.e., systematic, stratified, and cluster sampling). With regards to non-probability sampling, the chapter examines the most popular techniques used by researchers, namely accidental sampling, purposive sampling, snowball sampling, and quota sampling.
Sample size is also discussed in detail, with a focus on the factors required to determine the appropriate size: the homogeneity of the sample, the number of variables under study, and the desired degree of accuracy.