Clustered sampling is a sampling technique based on dividing the whole population into groups (“clusters”), then using random sampling to select elements from the groups.
For example, if the target population is the whole population of a city, a researcher might select 100 households at random and to include all members of each houshold in the sample. The reason is that a households represent various types of populations, e.g. children and adults, housewives and working women – because a great part of the whole population belongs to such households.