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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 widely used probability sampling technique in research, especially in large-scale studies where obtaining data from every individual in the population is impractical. It offers an efficient way to collect data while maintaining statistical rigor.
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.
What is Cluster Sampling? 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 a statistical method used when studying large populations, especially when individual elements are not easily accessible. Unlike simple random sampling, where each member of the population has an equal chance of being selected, cluster sampling divides the population into groups, or 'clusters', before making a random selection.
Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups (clusters) for research. So, researchers then select random groups with a simple random or systematic random sampling technique for data collection and unit of analysis.
Cluster sampling (also known as one-stage cluster sampling) is a technique in which clusters of participants representing the population are identified and included in the sample. This is a popular method in conducting marketing researches.
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.
What is Cluster Sampling in Statistics? Cluster sampling is a technique often employed when a researcher isn’t able to gather data from an entire population or geographic area. Why? Surveying a large area can be expensive and time-consuming; it also makes analysis much more complicated.