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  2. Measurement uncertainty - Wikipedia

    en.wikipedia.org/wiki/Measurement_uncertainty

    In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale.. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.

  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. Experimental uncertainty analysis - Wikipedia

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

    In Figure 7 are the PDFs for Method 1, and it is seen that the means converge toward the correct g value of 9.8 m/s 2 as the number of measurements increases, and the variance also decreases. From this it is concluded that Method 1 is the preferred approach to processing the pendulum or other data.

  5. Uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_analysis

    In physical experiments uncertainty analysis, or experimental uncertainty assessment, deals with assessing the uncertainty in a measurement.An experiment designed to determine an effect, demonstrate a law, or estimate the numerical value of a physical variable will be affected by errors due to instrumentation, methodology, presence of confounding effects and so on.

  6. Uncertainty quantification - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_quantification

    Given some experimental measurements of a system and some computer simulation results from its mathematical model, inverse uncertainty quantification estimates the discrepancy between the experiment and the mathematical model (which is called bias correction), and estimates the values of unknown parameters in the model if there are any (which ...

  7. Probability bounds analysis - Wikipedia

    en.wikipedia.org/wiki/Probability_bounds_analysis

    The probability that an uncertain number represented by a p-box D is less than zero is the interval Pr(D < 0) = [F(0), F̅(0)], where F̅(0) is the left bound of the probability box D and F(0) is its right bound, both evaluated at zero. Two uncertain numbers represented by probability boxes may then be compared for numerical magnitude with the ...

  8. Explainer-How Trump could bypass the Senate to install his ...

    www.aol.com/news/explainer-trump-could-bypass...

    By Andy Sullivan. WASHINGTON - President-elect Donald Trump has said he might install his picks for top administration posts without first winning approval in the U.S. Senate.

  9. Uncertainty budget - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_budget

    A different measured value arises for the measurement uncertainty with each new measurement. The measurement uncertainty budget must be re-determined for each measured value. Examples. 1. A measured temperature value is read every day. Decisive influencing variables are ambient temperature and air pressure, which can vary every day. 2.