The Central Limit Theorem states that for a sufficiently large sample the sampling distribution of the means of all possible samples of size n generated from the population will be approximately normally distributed with the mean of the sampling distribution equal to $\sigma$² and the variance equal to $\sigma$^2/n.

Question

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The Central Limit Theorem states that the mean of the sampling distribution is equal to the population mean ($\mu$), and the variance is equal to $\sigma^2/n$, where $\sigma^2$ is the population variance.

The Central Limit Theorem States That for a Sufficiently Large σ\sigmaσ

The Central Limit Theorem States That for a Sufficiently Large $\sigma$