Question

Describe cluster sampling by giving an example

Answer 1

Cluster sampling is defined as a sampling method where multiple clusters of people are created from a population where they are indicative of homogeneous characteristics and have an equal chance of being a part of the sample. In this sampling method, a simple random sample is created from the different clusters in the population. Basically, a simple random sample of the clusters is chosen and this constitutes the sample. This is different from Stratified Sampling in the way that Stratified Sampling picks atleast one sample item from each of the strata, whereas here, some of the clusters remain unchosen and unrepresented.

An example has been explained below for your reference.

For example, if a person wants to conduct a study to judge the performance of sophomore’s in business education across the US, it is impossible to conduct a research study that involves a sophomore in every university in the US. Instead, by using cluster sampling, the researcher can club the universities from each city into one cluster. These clusters then define all the sophomore student population in the US. Next, either using simple random sampling or systematic random sampling, some clusters can be picked for the research study. Subsequently, by using simple or systematic sampling, sophomore’s from each of these selected clusters can be picked or the whole clusters can be included on whom to conduct the research study.