The Central Limit Theorem (CLT) is a fundamental concept in statistics that states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the shape of the population distribution. In practical terms, this means that for sufficiently large sample sizes, the distribution of sample means will be approximately normal, even if the underlying population distribution is not normally distributed.

Understanding the Central Limit Theorem is key to making sense of the randomness in data. 📈🔬 #CentralLimitTheorem #Statistics #MentalModels

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