In this module you will begin the study of inferential statistics. That is when information from a sample is used to draw inferences about a population. For example, if 48% of people in a random sample of voters support a proposal that will be on the ballot in an upcoming election, we expect that about 48% of people that vote on election day will support the proposal. But we don’t expect that exactly 48% of votes will be “yes.”  Our estimate is likely to be off by a little. We often calculate an interval, or range of values, that is likely to capture the true percentage of voters that will cast a “yes” ballot. For this we need to use interval notation. We’ll also review some terminology and formulas you learned earlier: population parameters and sample statistics, and calculations for population and sample mean, variance and standard deviation.