What is the difference between cluster and stratified sampling?

In summary, the difference between cluster and stratified sampling lies in how the test population is sampled and divided. Cluster sampling involves dividing the population into groups and randomly selecting clusters to sample from, while stratified sampling involves dividing the population into groups and randomly selecting individuals from each group. When deciding which method to use, it is important to consider the specific needs and preferences of the person making the decision.