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Sampling Variability - MathBitsNotebook(A2)

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When using samples from a large population to determine information about the population parameters, the samples must be randomly chosen, must be of the same size (not smaller than 30), and the more samples that are used, the more reliable the information gathered will be. When dealing with a large number of samples (of the same size) that yield different results for a specific statistic (such as ), statisticians need to determine which of the samples' results will be the "best" choice to represent the population. This choice is determined by examining all of the possible samples (of the same size) for a specific statistic (such as ) and calculating the average (mean) of that statistic (). In this way, the best "estimate" of the true population parameter will be discovered. This modeling process is a Sampling Distribution of the Sample Means. In an attempt to obtain this "best" choice of a statistic, a graph may be prepared to visualize what is happening with that statistic in relation

Sampling Variability - MathBitsNotebook(A2) Sampling Variability and Sampling Distribution Models MathBitsNotebook.com Topical Outline | Algebra 2 Outline | MathBits' Teacher Resources Terms of Use Contact Person: Donna Roberts Sampling Variability: In a real world problem, the statistical information relating to large populations (called parameters ) is unknown. Random samples from these large populations are used to estimate information about the population parameters. The term "sampling variability" refers to the fact that the statistical information from a sample (called a statistic ) will

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