Random Sampling

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What is random sampling?

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Random sampling is a technique used to select a subset of individuals from a larger population, where each individual has an equal chance of being chosen.

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Why is it important for a sample to be representative?

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A representative sample accurately reflects the characteristics of the larger population, ensuring that the results of a study or survey can be generalized.

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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, often due to the method of selection.

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What is the difference between random sampling and convenience sampling?

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Random sampling involves selecting individuals randomly from the population, while convenience sampling involves selecting individuals who are easiest to reach.

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What is stratified sampling?

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Stratified sampling is a method where the population is divided into subgroups (strata) and random samples are taken from each stratum.

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What is systematic sampling?

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Systematic sampling involves selecting every nth individual from a list of the population.

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What is the purpose of using random sampling in surveys?

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The purpose is to minimize bias and ensure that the sample reflects the diversity of the population.

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What is a sample size?

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Sample size refers to the number of individuals included in a sample, which affects the reliability of the results.

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What is the significance of the Central Limit Theorem in random sampling?

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The Central Limit Theorem states that the distribution of sample means approaches a normal distribution as the sample size increases, regardless of the population's distribution.

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What is a sampling error?

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Sampling error is the difference between the sample statistic and the actual population parameter, often due to the sample not being representative.