DIFFERENCES BETWEEN CLUSTER AND RANDOM SAMPLING

Cluster sampling and random sampling are two methods of selecting a sample from a population.

Cluster sampling involves dividing the population into clusters or groups and taking a sample from each cluster, while random sampling involves randomly selecting individuals from the population.

Cluster sampling generally has larger sample sizes as it includes all individuals within selected clusters, while random sampling can have smaller sample sizes as it only includes a random selection of individuals.

Cluster sampling can be more cost-effective, but it can also be more time-consuming to gather data from all individuals within selected clusters. Random sampling is generally considered more representative of the population as it includes a random selection of individuals from across the population, while cluster sampling may not capture variation within clusters.