The Purpose Of Cluster Sampling Is To Sample Economically While Retaining The Characteristics Of A Probability Sample. What Are The Problems Faced While Doing This?


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Syed Rizwan Ali Shah Hamdani Profile
The purpose of cluster sampling is to sample economically while retaining the characteristics of a probability sample. At the same time, Cluster sampling addresses following two problems:

1. Researchers lack a good sampling frame for a dispersed population and the cost to reach a sampled element is very high. A cluster is unit that contains final sampling elements but can be treated temporarily as a sampling element itself. A researcher first samples cluster, each of which contains elements, then draws a second sample from within the clusters selected in the first stage of sampling. In other words, the researcher randomly samples clusters, and then randomly samples elements from within the selected clusters. He or she can create a good sampling frame of clusters, even if it is impossible to create one for sampling elements. Once the researcher gets a sample of clusters, creating a sampling frame for elements within each cluster becomes more manageable.

2. A second advantage for geographically dispersed populations is that elements within each cluster are physically closer to each other. This may produce a savings in locating or reaching each element.

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