Sampling Bias

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 BiasDistinction From Selection Bias, Types of Sampling Bias, Problems Caused By Sampling Bias, Historical Examples, Statistical Corrections For A Biased Sample

Other articles related to "sampling bias, bias":

Selection Bias - Types - Sampling Bias
... Sampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than ... It is mostly classified as a subtype of selection bias, sometimes specifically termed sample selection bias, but some classify it as a separate type of bias ... A distinction, albeit not universally accepted, of sampling bias is that it undermines the external validity of a test (the ability of its results to be generalized to the rest of the ...
sample" class="article_title_2">Sampling Bias - Statistical Corrections For A Biased Sample
... If entire segments of the population are excluded from a sample, then there are no adjustments that can produce estimates that are representative of the entire population ... But if some groups are underrepresented and the degree of underrepresentation can be quantified, then sample weights can correct the bias ...

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