Interval Estimation

Method Inductive Reasoning Generalizing from a specific idea/notion/data-point Start: a statistic is used as a “best point estimate” for a corresponding parameter, when it is computed using a random sample of data. To generalize, we add and subtract a “margin for error” that creates a range of values for the parameter. This range is called the interval estimate The width of the interval estimate is the product of 2 things: The level of confidence, AND The standard error of the statistic

Assumptions Data sample must be randomly selected The size of the sample ought to be as large as possible, and should contain at least 30 observations—according to Central Limit Theorem. If a sample is either not randomly selected or not large enough, then an interval estimate may fail to yield a valid generalization about a parameter’s value.