Sampling Techniques

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What is a Stratified Random Sample?

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A sampling method where the population is divided into subgroups (strata) and random samples are taken from each stratum to ensure representation.

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What is a Simple Random Sample?

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A sampling method where every member of the population has an equal chance of being selected, typically achieved using random number generators.

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What is a Cluster Sample?

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A sampling technique where the population is divided into clusters (groups), and entire clusters are randomly selected for the sample.

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What is a Convenience Sample?

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A sampling method that involves selecting individuals who are easiest to reach, which may lead to bias.

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What is a Systematic Sample?

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A sampling method where members of the population are selected at regular intervals, such as every nth individual.

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What is the purpose of using sampling techniques?

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To gather data from a subset of a population to make inferences about the entire population without surveying everyone.

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How does a Stratified Random Sample differ from a Simple Random Sample?

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Stratified Random Sampling ensures representation from different subgroups, while Simple Random Sampling does not consider subgroups.

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What is the importance of random selection in sampling?

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Random selection helps to eliminate bias and ensures that the sample is representative of the population.

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What is an example of a situation where a Cluster Sample would be appropriate?

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When surveying students in a school, selecting entire classes (clusters) rather than individual students.

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What is the main disadvantage of a Convenience Sample?

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It may not accurately represent the population, leading to biased results.