In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others. It results in a biased sample, a non-random 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.
Read more about Sampling Bias: Distinction From Selection Bias, Types of Sampling Bias, Problems Caused By Sampling Bias, Historical Examples, Statistical Corrections For A Biased Sample
Famous quotes containing the word bias:
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—Ralph Waldo Emerson (1803–1882)