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  2. Calibration (statistics) - Wikipedia

    en.wikipedia.org/wiki/Calibration_(statistics)

    In addition, calibration is used in statistics with the usual general meaning of calibration. For example, model calibration can be also used to refer to Bayesian inference about the value of a model's parameters, given some data set, or more generally to any type of fitting of a statistical model.

  3. Calibration - Wikipedia

    en.wikipedia.org/wiki/Calibration

    The formal definition of calibration by the International Bureau of Weights and Measures (BIPM) is the following: "Operation that, under specified conditions, in a first step, establishes a relation between the quantity values with measurement uncertainties provided by measurement standards and corresponding indications with associated measurement uncertainties (of the calibrated instrument or ...

  4. Calibrated probability assessment - Wikipedia

    en.wikipedia.org/wiki/Calibrated_probability...

    Calibration training is used to increase a person’s ability to provide accurate estimates for stochastic methods. Research found that most people could be calibrated if they took the time and that a person’s calibration i.e. performance in providing accurate estimates, carries over to estimates provided for content outside of the ...

  5. Calibration curve - Wikipedia

    en.wikipedia.org/wiki/Calibration_curve

    A calibration curve plot showing limit of detection (LOD), limit of quantification (LOQ), dynamic range, and limit of linearity (LOL).. In analytical chemistry, a calibration curve, also known as a standard curve, is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration. [1]

  6. Accuracy and precision - Wikipedia

    en.wikipedia.org/wiki/Accuracy_and_precision

    The field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both.

  7. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In hydrogeology, RMSD and NRMSD are used to evaluate the calibration of a groundwater model. [7] In imaging science, the RMSD is part of the peak signal-to-noise ratio, a measure used to assess how well a method to reconstruct an image performs relative to the original image.

  8. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    When either randomness or uncertainty modeled by probability theory is attributed to such errors, they are "errors" in the sense in which that term is used in statistics; see errors and residuals in statistics. Every time a measurement is repeated, slightly different results are obtained.

  9. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    the jackknife procedure, used to estimate biases of sample statistics and to estimate variances, and; cross-validation, in which the parameters (e.g., regression weights, factor loadings) that are estimated in one subsample are applied to another subsample. For more details see resampling.