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Stratified sampling is the most suitable technique when the population is divided into distinct subgroups (strata), and it is crucial to ensure that each subgroup is represented proportionally. In this method, the population is first divided into homogeneous subgroups based on a characteristic (e.g., age, income, education), and then a random sample is drawn from each subgroup. This ensures that the sample accurately represents the entire population, especially when certain subgroups are underrepresented in a simple random sample. Option A is incorrect because simple random sampling does not ensure proportional representation of subgroups. Option C is incorrect because cluster sampling divides the population into clusters, which may not necessarily represent subgroups proportionally. Option D is incorrect because systematic sampling involves selecting every nth element from a population, which does not guarantee proportional subgroup representation. Option E is incorrect because convenience sampling involves selecting individuals who are easiest to reach, which does not guarantee a representative sample.
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