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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 or 3 σ, 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 ...

  3. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    Download as PDF; Printable version; In other projects ... for example in demand data) because there would be a division by zero or values of MAPE tending to infinity ...

  4. Error bar - Wikipedia

    en.wikipedia.org/wiki/Error_bar

    Download as PDF; Printable version; ... These quantities are not the same and so the measure selected should be stated explicitly in the graph or supporting text ...

  5. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    For a confidence level, there is a corresponding confidence interval about the mean , that is, the interval [, +] within which values of should fall with probability . ...

  6. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

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  7. Error vector magnitude - Wikipedia

    en.wikipedia.org/wiki/Error_Vector_Magnitude

    EVM is generally expressed in percent by multiplying the ratio by 100. [ 1 ] The ideal signal amplitude reference can either be the maximum ideal signal amplitude of the constellation, or it can be the root mean square (RMS) average amplitude of all possible ideal signal amplitude values in the constellation.

  8. Mean absolute error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_error

    Quantity disagreement is the absolute value of the mean error: [4] | = |. Allocation disagreement is MAE minus quantity disagreement. It is also possible to identify the types of difference by looking at an ( x , y ) {\displaystyle (x,y)} plot.

  9. 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%.