Solved Examples on Cluster Random Sampling
Example 1: Given Total Population: 800 households, Number of Clusters: 40 and Average Cluster Size (ACS) is 20, then determine the sample size using cluster random sampling.
Solution:
As we know, n = ACS × Number of clusters
⇒ n = 20 × 40
⇒ n = 800
Thus, the required sample size is 800 households.
Example 2: Given Schools in District: 60, Average Cluster Size: 15, Desired Sample Size: 300 then determine how many clusters should be randomly selected?
Solution:
Number of Clusters = Desired Sample Size/ ACS
⇒ Number of Clusters = 300 / 15
⇒ Number of Clusters =20
Thus, 20 schools were selected per clusters for the survey.
Example 3: Given hospitals in region is 25, desired sample size is 150 and average Cluster Size is 10 then determine the total number of elements in the sample.
Solution:
Hospitals in Region = 25
Desired Sample Size = 150
Average Cluster Size = 10
Thus, Total Sample Size = Desired Sample Size × ACS
⇒ Total Sample Size = 150 × 10
⇒ Total Sample Size = 1500
Thus, the sample consists of 1500 healthcare elements.
Cluster Random Sampling
Cluster Random Sampling is a method where we start by picking a whole group and then study everyone within that group. It’s not like simple random sampling, where we select people one by one.
It is also known as Cluster Sampling. In cluster random sampling, these groups are what we focus on. This article takes you through cluster sampling, explaining what it is, the different types, how it works, and where it’s commonly used.