Question

Cluster sampling and stratified sampling both involve selecting subjects in subgroups of population. What's the difference between those two types of sampling?

Answer 1

With cluster​ sampling, all members of randomly selected subgroups​ (or clusters) are​ selected, but with stratified​ sampling, samples from each of the different subgroups​ (or strata) are selected.

Answer 2

Step-by-step explanation:

In cluster sampling the target population is divided into clusters. Some of the clusters are selected randomly and subjects are also selected randomly.

In stratified sampling the target population is divided into homogenous strata and the members are selected randomly.

Cluster sampling and stratified sampling both processes of sampling involves the selecting the subjects in the subgroups of the desire population. In cluster sampling all the subjects of the subgroup are studied, whereas in the case of the stratified sampling only the randomly selected subjects of the subgroups are chosen and studied.