Type A and Type B Evaluation of Uncertainty
Knowledge about an input quantity is inferred from repeated measured values (Type A evaluation of uncertainty), or scientific judgement or other information concerning the possible values of the quantity (Type B evaluation of uncertainty).
In Type A evaluations of measurement uncertainty, the assumption is often made that the distribution best describing an input quantity given repeated measured values of it (obtained independently) is a Gaussian distribution. then has expectation equal to the average measured value and standard deviation equal to the standard deviation of the average. When the uncertainty is evaluated from a small number of measured values (regarded as instances of a quantity characterized by a Gaussian distribution), the corresponding distribution can be taken as a -distribution. Other considerations apply when the measured values are not obtained independently.
For a Type B evaluation of uncertainty, often the only available information is that lies in a specified interval . In such a case, knowledge of the quantity can be characterized by a rectangular probability distribution with limits and . If different information were available, a probability distribution consistent with that information would be used.
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