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# Central Limit Theorem

## The central limit theorem states that the sampling distribution of any statistic will be normal or nearly normal, if the sample size is large enough.

Levels are CK-12's student achievement levels.
Basic Students matched to this level have a partial mastery of prerequisite knowledge and skills fundamental for proficient work.
At Grade (Proficient) Students matched to this level have demonstrated competency over challenging subject matter, including subject matter knowledge, application of such knowledge to real-world situations, and analytical skills appropriate to subject matter.
Advanced Students matched to this level are ready for material that requires superior performance and mastery.

## Central Limit Theorem

This Concept introduces students to the Central Limit Theorem.

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## Sampling Distribution of the Sample Mean

Shows how to find the probability of having a certain weight or range of weights based on the distribution when you know the mean weight and standard deviation of a distribution.

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## Distribution of Sample Mean

Explores how to find the sample mean and standard deviation using the Central Limit Theorem when given information about the population mean and standard deviation.

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## Application of the Central Limit Theorem, Part 1

Looks at how to calculate the probability of finding someone with a certain shower time or above given information about the population mean and standard deviation of shower times.

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## Application of the Central Limit Theorem, Part 2

Part 2 in calculating the probability of finding someone with a certain shower time or above given information about the population mean and standard deviation of shower times.

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