Sampling Distribution

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  • The resulting distribution of a sampled statistic (proportion, mean, variance, or their respective differences, etc.) from random samples of a given size (n). The sampling distribution has all the characteristics of any distribution, including measures of centrality, variability, and shape. The central limit theorem provides the basis for expecting a sampling distribution of a sampled statistic to become more like a normal distribution with reduced sampling error as sample size increases. The mean of the sampling distribution is expected to be the mean of the population from which the samples are randomly drawn.

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