Question
Cluster v/s Stratified sampling techniqu
Answer :
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Cluster sampling and stratified sampling are both probability sampling techniques widely used in marketing research, but they differ significantly in their approach, purpose, and application. Stratified sampling involves dividing the entire population into homogeneous subgroups known as strata based on specific characteristics such as age, income, gender, or geographic location. Once the population is segmented, samples are drawn from each stratum, either proportionately or disproportionately, ensuring that all relevant subgroups are adequately represented. This method enhances the accuracy and reliability of the results because it reduces sampling error and ensures representation of diverse population segments, which is particularly useful when the researcher knows that certain subgroups vary significantly in behavior or preferences. On the other hand, cluster sampling involves dividing the population into clusters, which are usually heterogeneous groups that ideally resemble the entire population. These clusters are often based on natural groupings such as cities, schools,
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