Sampling bias

A pie chart showing the results of a hypothetical survey, in which the question asked was "Do you enjoy responding to surveys?" The chart shows that 99.8 percent of participants said, "Yes, I love responding to surveys!" and that 0.2 percent said "No, I throw them in the trash" — An example of a biased sample in a hypothetical population survey, which asks if participants like responding to surveys, thus selecting for the individuals who were most likely to respond in the first place

In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling.

Medical sources sometimes refer to sampling bias as ascertainment bias. Ascertainment bias has basically the same definition, but is still sometimes classified as a separate type of bias.