Sampling Methods

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What is stratified sampling?

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Stratified sampling is a method of sampling that involves dividing a population into subgroups (strata) based on shared characteristics, and then randomly selecting samples from each stratum.

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What is convenience sampling?

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Convenience sampling is a non-probability sampling method where samples are selected based on their easy availability and proximity to the researcher.

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What is cluster sampling?

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Cluster sampling is a sampling technique where the population is divided into clusters (usually geographically), and entire clusters are randomly selected to be included in the sample.

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What is systematic sampling?

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Systematic sampling is a method where samples are selected at regular intervals from a sorted list of the population, such as every nth individual.

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What is the difference between stratified and cluster sampling?

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Stratified sampling involves dividing the population into strata and sampling from each, while cluster sampling involves dividing the population into clusters and sampling entire clusters.

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What are the advantages of stratified sampling?

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Stratified sampling can lead to more accurate and reliable results by ensuring that all subgroups are represented in the sample.

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What are the disadvantages of convenience sampling?

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Convenience sampling can lead to biased results as it may not accurately represent the entire population.

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When is cluster sampling most useful?

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Cluster sampling is most useful when the population is large and spread out geographically, making it impractical to conduct a simple random sample.

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What is a sampling frame?

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A sampling frame is a list or database from which a sample is drawn, representing the population of interest.

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What is the purpose of sampling in research?

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The purpose of sampling is to select a subset of individuals from a population to estimate characteristics or behaviors of the entire population.