Upon successful completion of this unit, you will be able to:

[1] apply the central limit theorem to approximate sampling distributions; [2] describe the role of sampling distributions in inferential statistics; [3] interpret a probability distribution for the mean of a discrete variable; [4] describe a sampling distribution in terms of repeated sampling; [5] compute the mean and standard deviation of the sampling distribution of population proportion p and mean; [6] approximate a sampling distribution based on the properties of the population; [7] compare the sampling distributions of different sample sizes