Cluster sampling is a probability sampling technique in which all population elements are categorized into mutually exclusive and exhaustive groups called clusters. Clusters are selected for sampling, and all or some elements from selected clusters comprise the sample. This method is typically used when natural groups exist in the population (e.g., schools or counties) or when obtaining a list of all population elements is impossible or impractically costly. As compared to simple random sampling, cluster sampling can reduce travel cost for in-person data collection by using geographically concentrated clusters. At the same time, cluster sampling is generally less precise than simple random or stratified sampling; therefore, it is typically used when it is economically justified (i.e., when a dispersed population would be expensive to survey). ...
Looks like you do not have access to this content.