This type of sampling method is called cluster sampling. With cluster sampling, the researcher divides the population into distinct group so called clusters. Then, a simple random sample of clusters is particular from the population. The researcher conducts his investigation on data from the sampled clusters. Paralleled to simple random sampling and stratified sampling, cluster sampling has advantages and disadvantages. For example, given equal sample sizes, cluster sampling usually makes available less precision than either simple random sampling or stratified sampling. On the other hand, if travel costs between clusters are high, cluster sampling may be further cost-effective than the other methods.
