Answer:
A. Cluster
Explanation:
Cluster sampling makes reference to a technique of sampling. The researcher splits the population into different groups through cluster selection, called clusters.
Next, a simple random selection of clusters is selected from the population. The researcher performs his study of sampled cluster data.
Cluster sampling has advantages and disadvantages comparable to simple random sampling and stratified sampling.
Cluster sampling, for example, is typically less reliable than either simple random sampling or stratified sampling given equal sample sizes.
On the other hand, if cluster travel costs are high, cluster sampling could be more price-effective than other approaches.