● Sampling distribution - Different random samples give different values for a statistic. The sampling distribution model model shows the behavior of the statistic over all the possible samples for the same size n. ● Central Limit Theorem - The Central Limit Theorem states that the sampling distribution model of the sample mean from a random sample is approximately Normal for large n, regardless of the distribution of the population, as long as the observations are independent. ● Sampling distribution - If assumptions of independence and random sampling are met, and we expect at least a model for a proportion 10 successes and 10 failures, then the sampling distribution of a proportion is modeled by a Normal.