What is Cluster Sampling?

Data Science, AI and ML
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#1

What is Cluster Sampling?

#2

Entire population is divided into different clusters and then clusters are randomly selected.

In one stage,entire cluster is selected randomly for sampling.

In second stage,here we first randomly select the clusters,combine those clusters and then randomly select samples from them.

How you do cluster sampling?

  1. Estimate a population parameter.
  2. Compute sample variance within each cluster (for two-stage cluster sampling).
  3. Compute standard error.
  4. Specify a confidence level.
  5. Find the critical value (often z-score or a t-score).
  6. Compute margin of error.

Cluster sampling is less expensive and more quick.
ref:https://medium.com/@rudly.raphael/all-you-need-to-know-about-cluster-sampling-f0dbb5592106

#3

Cluster sampling (also known as one-stage cluster sampling) is a technique in which clusters of participants that represent the population are identified and included in the sample. Cluster sampling involves identification of cluster of participants representing the population and their inclusion in the sample group. This is a popular method 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.