Central Limit Theorem (CLT): For sufficiently large n, the sampling distribution of x-bar is approximately normal regardless of the population shape.
How to apply it: The CLT is the reason we can use normal-based inference even when the population is not normal; n >= 30 is a common guideline.
Course: AP Statistics · Unit: Sampling Distributions
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