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  2. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

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  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. Mean absolute error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_error

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  5. Blocking (statistics) - Wikipedia

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

    μ is the general location parameter (i.e., the mean) T i is the effect for being in treatment i (of factor X 1 ) B j is the effect for being in block j (of factor X 2 )

  6. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.

  7. Bootstrapping (statistics) - Wikipedia

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

    (The sample mean need not be a consistent estimator for any population mean, because no mean needs to exist for a heavy-tailed distribution.) A well-defined and robust statistic for the central tendency is the sample median, which is consistent and median-unbiased for the population median.

  8. Error bar - Wikipedia

    en.wikipedia.org/wiki/Error_bar

    This statistics -related article is a stub. You can help Wikipedia by expanding it.

  9. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or of an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).