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  2. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

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  3. Error bar - Wikipedia

    en.wikipedia.org/wiki/Error_bar

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  4. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    Excel maintains 15 figures in its numbers, but they are not always accurate; mathematically, the bottom line should be the same as the top line, in 'fp-math' the step '1 + 1/9000' leads to a rounding up as the first bit of the 14 bit tail '10111000110010' of the mantissa falling off the table when adding 1 is a '1', this up-rounding is not undone when subtracting the 1 again, since there is no ...

  5. 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).

  6. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    This interval is called the confidence interval, and the radius (half the interval) is called the margin of error, corresponding to a 95% confidence level. Generally, at a confidence level , a sample sized of a population having expected standard deviation has a margin of error

  7. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    CEP is not a good measure of accuracy when this distribution behavior is not met. Munitions may also have larger standard deviation of range errors than the standard deviation of azimuth (deflection) errors, resulting in an elliptical confidence region. Munition samples may not be exactly on target, that is, the mean vector will not be (0,0).

  8. Residual sum of squares - Wikipedia

    en.wikipedia.org/wiki/Residual_sum_of_squares

    Residual sum of squares. In statistics, the residual sum of squares ( RSS ), also known as the sum of squared residuals ( SSR) or the sum of squared estimate of errors ( SSE ), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation ...

  9. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    The statistical errors, on the other hand, are independent, and their sum within the random sample is almost surely not zero. One can standardize statistical errors (especially of a normal distribution) in a z-score (or "standard score"), and standardize residuals in a t-statistic, or more generally studentized residuals.