Sampling Techniques and Methods

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What is a biased sample?

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A biased sample is one that does not accurately represent the population from which it is drawn, leading to skewed results. For example, asking only members of a baseball team about their favorite sport is biased.

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What is a stratified sample?

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A stratified sample is selected by dividing the population into subgroups (strata) and then taking a fixed number of units from each group using a simple random sample.

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What is systematic sampling?

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Systematic sampling involves ordering the population in some way and then selecting every k-th unit from that ordered list.

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What is a simple random sample (SRS)?

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A simple random sample is a sampling method where every possible group of units of the required size has the same chance of being selected.

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What is a cluster sample?

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A cluster sample involves dividing the population into clusters (usually geographically) and then randomly selecting entire clusters to sample.

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What is the difference between probability and non-probability sampling?

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Probability sampling involves random selection, allowing for the calculation of sampling error, while non-probability sampling does not involve random selection and may lead to bias.

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What is convenience sampling?

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Convenience sampling is a non-probability sampling method where samples are taken from a group that is easily accessible.

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What is the purpose of sampling?

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The purpose of sampling is to gather data from a subset of a population to make inferences about the entire population.

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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.

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What is the importance of sample size?

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Sample size is crucial because larger samples tend to provide more accurate estimates of the population parameters and reduce sampling error.

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