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  2. Experimental uncertainty analysis - Wikipedia

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

    Systematic errors in the measurement of experimental quantities leads to bias in the derived quantity, the magnitude of which is calculated using Eq(6) or Eq(7). However, there is also a more subtle form of bias that can occur even if the input, measured, quantities are unbiased; all terms after the first in Eq(14) represent this bias.

  3. File:Measurement distribution with systematic and random ...

    en.wikipedia.org/wiki/File:Measurement...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  4. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    Upload file; Search. Search. Appearance. Donate; ... Download as PDF; Printable version; ... discusses systematic and random errors in considerable detail. In fact ...

  5. Westgard rules - Wikipedia

    en.wikipedia.org/wiki/Westgard_Rules

    The Westgard rules are a set of statistical patterns, each being unlikely to occur by random variability, thereby raising a suspicion of faulty accuracy or precision of the measurement system. They are used for laboratory quality control, in "runs" consisting of measurements of multiple samples.

  6. Accuracy and precision - Wikipedia

    en.wikipedia.org/wiki/Accuracy_and_precision

    While precision is a description of random errors (a measure of statistical variability), accuracy has two different definitions: More commonly, a description of systematic errors (a measure of statistical bias of a given measure of central tendency, such as the mean). In this definition of "accuracy", the concept is independent of "precision ...

  7. Data validation and reconciliation - Wikipedia

    en.wikipedia.org/wiki/Data_validation_and...

    Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.