052. The Central Limit Theorem

In many instances the population is not normally distributed. In such cases the Central Limit Theorem Is used. It is states the following:

As n gets larger, the sampling distribution of sample means will approach a normal distribution with = μ and .

This means that even if the population is not normally distributed, the distribution of sample means will be normal if N ≥ 30. This is because the standard error gets smaller as N gets bigger.

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