Cluster sampling is a statistical method used to select a sample from a larger population. In this approach, the population is divided into smaller groups, known as clusters, which are usually based on geographical areas or other natural groupings. Instead of sampling individuals from the entire population, researchers randomly select a few clusters and then collect data from all members within those chosen clusters. This method is often more practical and cost-effective, especially when the population is large and spread out. By focusing on specific clusters, researchers can save time and resources while still obtaining a representative sample of the overall population.