What are the main reason for using cluster sampling? What is the single and two stage of cluster sampling? Give an authentic scenario regarding the cluster sampling.
Chaim Ferguson
Answered question
2022-10-29
Answer & Explanation
getrdone07tl
Beginner2022-10-30Added 23 answers
Cluster sampling is a sampling method in which the entire population of the study is divided into externally homogeneous (similar), but internally heterogeneous (varied), group called clusters and each cluster is a mini representation of the entire population.
Answer:
The main reason for using cluster sampling is
- cost efficiency
- convenient access
- Data accuracy
- Ease of implementation
Single stage of cluster sampling:
In this, a simple random sample of clusters is selected and data are collected from every unit in the sampled clusters.
Two stage of cluster sampling:
In two stage sampling, simple random sampling is applied within each cluster to select a sub sample of elements in each cluster.
Scenario regarding the cluster sampling
In cluster sampling we group people in different way like natural grouping and each group is called a cluster. lets say I am going to interview group of people but one group lives in street 1, another group lives in street 2 and last group lives in street 3 so all the streets are in same neighborhood but I don't want to go around whole neighborhood cause its gonna take lot of time and I want to make the process easier so I will use SRS method to randomly choose one street , so street 1 is taken as 1,street 2 as 2 and street 3 as 3. After using SRS between 1, 2 and 3. I got number 3, which means street 3 is the cluster which I am going to interview all the people live in the street 3. so instead of interviewing all the groups here we have named each clusters as group. which made work lot easier this is called as cluster sampling.
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