Central Limit Theorem

Definition

The Central Limit Theorem states that as the sample size increases, the sampling distribution of the mean approaches a normal distribution regardless of the shape of the population distribution.

Related terms

Sampling Distribution: The probability distribution of a statistic obtained through repeated sampling from a population.

Standard Error: An estimate of how much variability exists between sample means when repeatedly taking samples from the same population.

Confidence Interval: A range around an estimated parameter value that is likely to contain the true parameter value with a certain level of confidence.