Cluster sampling may be used when it is either impossible or impractical to compile an exhaustive list of the elements that make up the target population. Usually, however, the population elements are already grouped into subpopulations and lists of those subpopulations already exist or can be created. For example, let's say the target population in a study was church members in the United States. There is no list of all church members in the country. The researcher could, however, create a list of churches in the United States, choose a sample of churches, and then obtain lists of members from those churches. Read more
about cluster sampling, the different types of cluster samples, and the advantages and disadvantages of using a cluster sample in social science research.
Other new articles posted this week that you might be interested in: Stratified Sampling and Systematic Sampling.