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Francesco Paucek

Feb 20, 2025

The central limit theorem defines large samples as having at least 36 elements. true or false.

The central limit theorem defines large samples as having at least 36 elements. true or false.
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It isFALSE that the Central Limit Theorem defines large samples as having at least36 elements. The central limit theorem(CLT) is a statistical theory that states that given a sufficiently largesample size from a population with a finite level of variance, the mean of allsamples from the same population will be approximately equal to the mean of thepopulation. I am hoping that this answer hassatisfied your query and it will be able to help you in your endeavor, and ifyou would like, feel free to ask another question.... Show More
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The statement that the Central Limit Theorem defines large samples as having at least 36 elements is false. The central limit theorem states that when samples from a data set with a known variance are aggregated their mean roughly equals the population mean. The Central Limit Theorem will apply if the number of samples is greater than  30.... Show More
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