Graham Beasley

Answered

2022-07-20

What is Cluster sampling and Explain with an example of research which uses cluster sampling.

Answer & Explanation

Osvaldo Crosby

Expert

2022-07-21Added 12 answers

Population is the complete set of people or objects with certain common characteristics under the study. The sample is the subset of population used to estimate the population parameters. Since complete enumeration of population units is time consuming and requires high manpower and high cost so, with the help of sampling, overcoming these drawbacks to estimate the population parameters. There are various method of sampling like simple random sampling, systematic sampling, cluster sampling, stratified sampling and convenience sampling method.

Cluster Sampling is the method of sampling in which the total population is divided into some recognizable sub-divisions called as clusters and then we will randomly select the clusters as a sample and then study each unit of these drawn clusters.

Advantages of cluster sampling:

- Since in this sampling method, the whole target population is divided into various groups( called as clusters) so, it consumes less work, time and cost.

- This method is quite convenient in nature and it is ease to implement.

- Since there could be large samples in each cluster so, the loss of accuracy in information per observation can be compensated.

- Disadvantages of cluster sampling:

If the clusters are not good representation of the population as whole then, this sampling method is not reliable.

This sampling method is quite complex in terms of planning as compared to other sampling method.

Cluster Sampling is the method of sampling in which the total population is divided into some recognizable sub-divisions called as clusters and then we will randomly select the clusters as a sample and then study each unit of these drawn clusters.

Advantages of cluster sampling:

- Since in this sampling method, the whole target population is divided into various groups( called as clusters) so, it consumes less work, time and cost.

- This method is quite convenient in nature and it is ease to implement.

- Since there could be large samples in each cluster so, the loss of accuracy in information per observation can be compensated.

- Disadvantages of cluster sampling:

If the clusters are not good representation of the population as whole then, this sampling method is not reliable.

This sampling method is quite complex in terms of planning as compared to other sampling method.

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