Cluster sampling is a technique that involves dividing a large and geographically dispersed population into smaller groups or clusters based on certain characteristics, and then randomly selecting these clusters to sample all individuals within them.
This method is useful in situations where it is not feasible to sample individuals from every area. However, there is a risk of bias if the selected clusters are not representative of the entire population.
Despite this, cluster sampling remains a cost-effective and time-efficient approach to sampling.
