Sampling is the process of selecting units (., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen. Let's begin by covering some of the key terms in sampling like "population" and "sampling frame." Then, because some types of sampling rely upon quantitative models, we'll talk about some of the statistical terms used in sampling . Finally, we'll discuss the major distinction between probability and Nonprobability sampling methods and work through the major types in each.
But panels have some limitations as well. They can be expensive to create and maintain, requiring more extensive technical skill and oversight than a single-shot survey. A second concern is that repeated questioning of the same individuals may yield different results than we would obtain with independent or “fresh” samples. If the same questions are asked repeatedly, respondents may remember their answers and feel some pressure to be consistent over time. Respondents might change their behavior because of questions you’ve asked; for example, questions about voting might spur them to register to vote. Respondents also become more skilled at answering particular kinds of questions. This may be beneficial in some instances, but to the extent it occurs, the panel results may be different from what would have been obtained from independent samples of people who have not had the practice in responding to surveys. A final disadvantage is that panelists may drop out over time, making the panel less representative of the target population as time passes if the kinds of people who drop out are different from those who tend to remain. For example, young people may move more frequently and thus be more likely to be lost to the panel when they move.