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  2. 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 ...

  3. Coefficient of restitution - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_restitution

    The COR is a property of a pair of objects in a collision, not a single object. If a given object collides with two different objects, each collision has its own COR. When a single object is described as having a given coefficient of restitution, as if it were an intrinsic property without reference to a second object, some assumptions have been made – for example that the collision is with ...

  4. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

    Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result, the formula can be used as a measure of the bias in the forecasts. A disadvantage of this measure is that it is undefined whenever a single actual value is zero.

  5. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    In computing, a roundoff error, [1] ... The condition number of a problem is the ratio of the relative change in the solution to the relative change in the input. [3]

  6. 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%.

  7. Experimental uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Experimental_uncertainty...

    (1) The Type I bias equations 1.1 and 1.2 are not affected by the sample size n. (2) Eq(1.4) is a re-arrangement of the second term in Eq(1.3). (3) The Type II bias and the variance and standard deviation all decrease with increasing sample size, and they also decrease, for a given sample size, when x's standard deviation σ becomes small ...

  8. Failure rate - Wikipedia

    en.wikipedia.org/wiki/Failure_rate

    When the failure rate is decreasing the coefficient of variation is ⩾ 1, and when the failure rate is increasing the coefficient of variation is ⩽ 1. [ clarification needed ] [ 15 ] Note that this result only holds when the failure rate is defined for all t ⩾ 0 [ 16 ] and that the converse result (coefficient of variation determining ...

  9. Approximation error - Wikipedia

    en.wikipedia.org/wiki/Approximation_error

    Best rational approximants for π (green circle), e (blue diamond), ϕ (pink oblong), (√3)/2 (grey hexagon), 1/√2 (red octagon) and 1/√3 (orange triangle) calculated from their continued fraction expansions, plotted as slopes y/x with errors from their true values (black dashes)