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  2. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  3. Acceptable quality limit - Wikipedia

    en.wikipedia.org/wiki/Acceptable_quality_limit

    The acceptable quality limit (AQL) is the worst tolerable process average (mean) in percentage or ratio that is still considered acceptable; that is, it is at an acceptable quality level. [1] Closely related terms are the rejectable quality limit and rejectable quality level (RQL).

  4. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

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  5. Symmetric mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Symmetric_mean_absolute...

    In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.

  6. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

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  7. Confidence region - Wikipedia

    en.wikipedia.org/wiki/Confidence_region

    The confidence region is calculated in such a way that if a set of measurements were repeated many times and a confidence region calculated in the same way on each set of measurements, then a certain percentage of the time (e.g. 95%) the confidence region would include the point representing the "true" values of the set of variables being estimated.

  8. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    Download as PDF; Printable version ... Each interval reflects the range within which one may ... the further from 50% the reported percentage, the smaller the margin ...

  9. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...