A worker wanted to estimate the average annual living expenses for the residents of New Zealand. He

Simple random sampling:
Simple random sampling is defined as a method of sampling in which, a sample of size n is drawn from a population of size N by using a random method, such as a random number table or software such as EXCEL, etc. to ensure that each of the N population units has the same probability of being selected in each draw. The simple random sampling gives a sample that is representative of the population.
Stratified sampling:
In stratified sampling, the entire heterogeneous population is divided into subpopulations. These subpopulations are called the strata’s. The samples within the strata’s are homogenous and the strata’s are different from each other. Samples are selected from each strata.
Cluster sampling:
Cluster sampling is defined as a method of sampling in which, at first, the entire population is divided into heterogeneous subgroups, especially by geographic areas called cluster, then desired number of clusters are selected from all the clusters, usually by simple random sampling. Here, all the units in the cluster is selected as sample. Each cluster is expected to be representative of the population.
Given,
A worker wanted to estimate the average annual living expenses for the residents of New Zealand. He randomly selected one of the suburbs and then collected the data for the annual living expenses for all residents.
Here, all the residents from randomly selected suburbs are considered as sample.
This is the example of cluster sampling.
Advantages of cluster sampling:
- Cluster sampling is cost effective and time effect that is less expensive and does not take more time.
- Cluster sampling allows accumulation of large samples.
- Cluster sample combine the advantages of both simple random sampling and stratified sampling.
- It allows us to collect information from one or more areas.
Disadvantages of cluster sampling:
-In cluster sample each cluster may have unequal size which results in sample size.
-Samples drawn using cluster sampling generally have high sampling error.