The sampling method in which a sample is selected by first dividing the population into groups and then selecting members from each group is known as:
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A. B. C. D.B
The population is divided into strata or subcategories and a sample is randomly selected from each strata.
The sampling method described in the question is known as cluster sampling, and the correct answer is C. Cluster sampling involves dividing the population into groups or clusters and then randomly selecting entire clusters as samples.
In cluster sampling, the population is divided into smaller, more manageable groups called clusters. These clusters are typically heterogeneous or diverse, meaning they have similar characteristics to the overall population. The clusters are usually geographically based, such as neighborhoods, schools, or organizations.
Once the clusters are defined, a subset of clusters is randomly selected to form the sample. The selection of clusters can be done using various methods such as simple random sampling, systematic random sampling, or probability proportional to size.
After selecting the clusters, all members within the selected clusters are included in the sample. This means that cluster sampling involves obtaining data from a subset of clusters, rather than collecting data from each individual within those clusters.
Cluster sampling is often used when the population is large and geographically dispersed, and it is impractical or costly to sample each individual. It can provide an efficient and cost-effective way of obtaining a representative sample by capturing the diversity within each selected cluster.
To summarize, cluster sampling involves dividing the population into clusters, randomly selecting clusters as samples, and including all members within the selected clusters in the sample. It is a useful method when the population is large and geographically diverse, and it offers advantages in terms of cost and feasibility.