Random Sampling Techniques

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What is Random Sampling?

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A technique used to select a subset of individuals from a larger population, ensuring that every individual has an equal chance of being chosen.

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What is Simple Random Sampling?

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A sampling method where every member of the population has an equal probability of being selected.

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What is Stratified Random Sampling?

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A sampling technique that involves dividing the population into subgroups (strata) and randomly selecting samples from each stratum.

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What is Systematic Random Sampling?

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A method where samples are selected at regular intervals from a randomly ordered list of the population.

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What is Cluster Random Sampling?

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A sampling technique where the population is divided into clusters, and entire clusters are randomly selected.

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When is Stratified Random Sampling most appropriate?

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When the population has distinct subgroups that need to be represented in the sample.

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What is the main advantage of Simple Random Sampling?

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It minimizes bias and ensures that every individual has an equal chance of selection.

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What is a disadvantage of Cluster Sampling?

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It may lead to higher sampling error if the clusters are not homogeneous.

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How does Systematic Sampling differ from Simple Random Sampling?

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Systematic Sampling selects individuals at regular intervals, while Simple Random Sampling selects individuals completely at random.

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What is the purpose of using Random Sampling techniques?

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To obtain a representative sample that can be used to make inferences about the entire population.