Cluster Sampling

Cluster sampling 150x150 Cluster Sampling Cluster sampling is a technique in which clusters of participants that represent the population are identified and included in the sample (Jackson, 2011). Cluster involves cluster of participants that represent the population are identified and included in the sample.  This is popular in conducting marketing researches.

The main aim of cluster sampling can be specified as cost reduction and increasing the levels of efficiency of sampling. This specific technique can also be applied in integration with multi-stage sampling.

A major difference between cluster and stratified sampling relates to the fact that in cluster sampling a cluster is perceived as a sampling unit, whereas in stratified  only specific elements of strata are accepted as sampling unit.

Area or geographical sampling can be specified as the most popular version of cluster sampling. Specifically, a specific area can be divided into clusters and primary data can be collected from each cluster to represent the viewpoint of the whole area.

The nature of cluster analysis depends on comparative size of separate clusters. If there are not major differences between sizes of clusters, then analysis can be facilitated by combining clusters. Alternatively, if there are vast differences in sizes of clusters probability proportionate to sample size can be applied to conduct the analysis.

 

Advantages

  • Is the most time-efficient and cost-efficient probability design for large geographical areas
  • This method is easy to be used from practicality viewpoint
  • Larger sample size can be used due to increased level of accessibility of perspective sample group members

 

Disadvantages 

  • Requires group-level information  to be known
  • Commonly has higher sampling error than alternative sampling techniques

 

 The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains explanation of advantages and disadvantages associated with each sampling technique and explains their application in greater details.

References 

Jackson, S.L. (2011) “Research Methods and Statistics: A Critical Approach” 4th edition, Cengage Learning