Define "sampling error."

The concept of sampling error specifically refers to the discrepancy that arises when the results obtained from a sample do not accurately reflect the characteristics of the entire population. This occurs because samples, by nature, are only subsets of a population, and if these subsets are not carefully selected to be representative, the sample results can skew the understanding of the population as a whole.

In research, a sample might inadvertently reflect certain biases or fail to include diverse groups, leading to outcomes that differ from the true population parameters. For instance, if a survey is conducted only among a specific demographic that does not represent the broader community, the findings may suggest trends or behaviors that are not applicable to the entire population. This highlights the importance of sampling techniques in research design to minimize sampling error and obtain more accurate data.

The other options reflect different concepts—selecting a representative group is part of the sampling process, participant errors are not related to sampling error but to survey administration, and reliability pertains to how consistently a measure produces similar results, which is a different aspect of research methodology.