What are the challenges and solutions of cluster sampling for geographically dispersed populations?
Cluster sampling is a technique that divides a population into smaller groups, or clusters, and selects a random sample of these clusters to represent the whole population. It is often used in quantitative research when the population is large, heterogeneous, and geographically dispersed. However, cluster sampling also poses some challenges and requires some solutions to ensure validity and reliability of the results. In this article, you will learn about some of the common challenges and solutions of cluster sampling for geographically dispersed populations.