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Cluster sampling is a method of probability sampling that is often used to study large populations, particularly those that are widely geographically dispersed. Researchers usually use pre-existing units such as schools or cities as their clusters.
Cluster sampling is a method of obtaining a representative sample from a population that researchers have divided into groups. An individual cluster is a subgroup that mirrors the diversity of the whole population while the set of clusters are similar to each other.
Cluster sampling is used when the target population is too large or spread out, and studying each subject would be costly, time-consuming, and improbable. Cluster sampling allows researchers to create smaller, more manageable subsections of the population with similar characteristics.
In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is selected.
Cluster sampling is a statistical sampling method used in research studies where the population is large and geographically dispersed. The cluster sampling method involves the following steps: Define the population: The first step in cluster sampling is to define the population of interest.
What is Cluster Sampling? Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups (clusters) for research.
In statistics, two of the most common methods used to obtain samples from a population are cluster sampling and stratified sampling. This tutorial provides a brief explanation of both sampling methods along with the similarities and differences between them.
Cluster sampling, a widely utilized technique in statistical research, offers a pragmatic approach to studying large populations where simple random sampling or systematic sampling may be impractical or costly.