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  2. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    For a confidence level, there is a corresponding confidence interval about the mean , that is, the interval [, +] within which values of should fall with probability . ...

  3. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    It is remarkable that the sum of squares of the residuals and the sample mean can be shown to be independent of each other, using, e.g. Basu's theorem.That fact, and the normal and chi-squared distributions given above form the basis of calculations involving the t-statistic:

  4. Confidence interval - Wikipedia

    en.wikipedia.org/wiki/Confidence_interval

    Welch [29] presented an example which clearly shows the difference between the theory of confidence intervals and other theories of interval estimation (including Fisher's fiducial intervals and objective Bayesian intervals). Robinson [30] called this example "[p]ossibly the best known counterexample for Neyman's version of confidence interval ...

  5. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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  6. Plus–minus sign - Wikipedia

    en.wikipedia.org/wiki/Plus–minus_sign

    In mathematical formulas, the ± symbol may be used to indicate a symbol that may be replaced by either of the plus and minus signs, + or −, allowing the formula to represent two values or two equations. [2] If x 2 = 9, one may give the solution as x = ±3. This indicates that the equation has two solutions: x = +3 and x = −3.

  7. Error analysis (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Error_analysis_(mathematics)

    The analysis of errors computed using the global positioning system is important for understanding how GPS works, and for knowing what magnitude errors should be expected.

  8. 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 ...

  9. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable.The general form of its probability density function is [2] [3] = ().