The Central Limit Theorem states that sample means approach a normal distribution as sample size grows, regardless of population shape. Statisticians, researchers, and analysts use it for confidence intervals, hypothesis testing, and quality control. It enables reliable inference from limited data, benefiting fields like medicine, finance, and social science.
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