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  2. Measurement uncertainty - Wikipedia

    en.wikipedia.org/wiki/Measurement_uncertainty

    Relative uncertainty is the measurement uncertainty relative to the magnitude of a particular single choice for the value for the measured quantity, when this choice is nonzero. This particular single choice is usually called the measured value, which may be optimal in some well-defined sense (e.g., a mean, median, or mode). Thus, the relative ...

  3. 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 ...

  4. 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)

  5. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    In this form the relative entropy generalizes (up to change in sign) both the discrete entropy, where the measure m is the counting measure, and the differential entropy, where the measure m is the Lebesgue measure. If the measure m is itself a probability distribution, the relative entropy is non-negative, and zero if p = m as measures.

  6. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_analysis

    The uncertainty on the output is described via uncertainty analysis (represented pdf on the output) and their relative importance is quantified via sensitivity analysis (represented by pie charts showing the proportion that each source of uncertainty contributes to the total uncertainty of the output).

  7. Kullback–Leibler divergence - Wikipedia

    en.wikipedia.org/wiki/Kullback–Leibler_divergence

    The relative entropy was introduced by Solomon Kullback and Richard Leibler in Kullback & Leibler (1951) as "the mean information for discrimination between and per observation from ", [6] where one is comparing two probability measures ,, and , are the hypotheses that one is selecting from measure , (respectively).

  8. Experimental uncertainty analysis - Wikipedia

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

    For example, an experimental uncertainty analysis of an undergraduate physics lab experiment in which a pendulum can estimate the value of the local gravitational acceleration constant g.

  9. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    With three or more choices in closer contention, choosing a correct formula for ... Measurement uncertainty; Random error; References Sources. Sudman, Seymour and ...