# Cluster Sampling Vs. Stratified Sampling: Differences Enlisted

There are various methods by which sampling can be done. This article will focus on cluster sampling vs. stratified sampling.
Palmira S
Last Updated: May 31, 2018
Cluster sampling and stratified sampling are two different sampling methods. The main difference between them is that a cluster is treated as sampling unit. Hence, in the first stage, analysis is done on a population of clusters. In stratified sampling, the elements within the strata are analyzed.
Cluster Sampling
• In this mode of sampling, the naturally occurring groups are selected for being included in the sample.
• Its main use is in market research. In this method, the total population is divided into samples or groups after which, a sample of the groups is selected.
• After this process, relevant and required data from all the elements of all the groups is collected.
• At times, instead of collecting information from each group, information can be collected from a sub-sample of the elements.
• If the variation is between the members of the groups and not between the actual groups, then this technique will work the best.
• Before you start using this methods on clusters, make sure that the clusters are collectively exhaustive and mutually exclusive.
Stratified Sampling
• In this technique, a sample is divided into stratum and on random basis.
• Different stratum are created, which will allow the usage of different sampling percentage in each stratum.
• These stratum are nothing but simple groups, which consists of a number of elements.
• On these stratum, simple random selection is performed.
• Make sure that every element is assigned only one stratum. This method is known to produce weighted mean whose variability is less than that of arithmetic mean of a simple random sample of the population.
• Even in stratified sampling, the strata should be collectively exhaustive and mutually exclusive.
• This will help in applying random or systematic sampling in each of the stratum. This will also help in the reduction of errors.
Cluster Vs. Stratified
Cluster Sampling
Application: It is used when natural groupings are evident in a statistical population.

Choice: It can be chosen if the group consists of homogeneous members.

Advantage: The method is cheaper as compared to the other methods.