A sampling frame is a collection of units from which a sample will be drawn. Ideally, the frame is identical to the population we want to learn about; more typically, the frame is only a subset of the population of interest. The difference between the frame and the population can be a source of bias in sampling design, if the parameter of interest has a different value for the frame than it does for the population. For example, one might desire to estimate the current annual average income of 1998 graduates of the University of California at Berkeley. I propose to use the sample mean income of a sample of graduates drawn at random. To facilitate taking the sample and contacting the graduates to obtain income information from them, I might draw names at random from the list of 1998 graduates for whom the alumni association has an accurate current address. The population is the collection of 1998 graduates; the frame is those graduates who have current addresses on file with the alumni association. If there is a tendency for graduates with higher incomes to have up-to-date addresses on file with the alumni association, that would introduce a positive bias into the annual average income estimated from the sample by the sample mean.