The Central Limit Theorem states that when the sample size increases, the distribution of the sample means will approach the normal distribution.

Central Limit Theorem

The theoretical foundation for \(\overline{x}\)-charts, which states that regardless of the distribution of the population of all parts or services, the x distribution tends to follow a normal curve as the number of samples increases.

Normal Distribution

A probability distribution that is symmetric around the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.