Sampling error refers to the possibility that a sample may not accurately represent the population due to chance factors, which can reduce validity, while sampling bias occurs when some members of the population are less likely or more likely to be included in the sample due to non-random factors, also reducing validity. Researchers can examine their sampling methods and determine if they introduced systematic bias or if differences are due to chance, and they can employ random sampling techniques and ensure all subgroups in a population have an equal chance of being included to help minimize error and bias.

1. Researchers distinguish between two factors [related to
sampling] that can reduce the validity of a study, sampling
error, and sampling bias. Can you explain the difference
between sampling error and sampling bias? How does each of
these factors relate to validity? How can researchers determine
if sampling error or sampling bias is affecting a study? Finally,
how might researchers best deal with sampling error and/or
sampling bias?