Beta Error
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Beta Error
When testing a hypothesis, the risk of a false negative in the results. It is also called a type II error or beta risk. See also:
Alpha risk.
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References in periodicals archive
My editorial merely explains the meaning of alpha and beta errors, and highlights the inherent uncertainty in statistical analysis, culminating in the statement that P values "do not provide proofs".
In calculating probabilities using a Bayesian approach, it is necessary to know not only the alpha and beta errors, but also the 'prior probability' (2).
This relationship has long been characterized by Type I and Type 11 errors, also known as Alpha and
Beta errors, respectively.
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