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  2. Technique for human error-rate prediction - Wikipedia

    en.wikipedia.org/wiki/Technique_for_human_error...

    In order for the final HEP calculation to be valid, the following assumptions are required to be fulfilled: There exists a seismic event initiator that leads to the establishment of air-based ventilation on the ITP processing tanks 48 and 49, possibly 50 in some cases.

  3. Probability of error - Wikipedia

    en.wikipedia.org/wiki/Probability_of_error

    In statistics, the term "error" arises in two ways. ... Thus distribution can be used to calculate the probabilities of errors with values within any given range.

  4. 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.

  5. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

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

  6. 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 . ...

  7. 'One of the worst' wrongful convictions: Man falsely IDed ...

    www.aol.com/one-worst-wrongful-convictions-man...

    These kinds of eyewitness errors are common in wrongful conviction cases. The Innocence Projects says that eyewitness misidentification played a role in 69% of convictions overturned by DNA evidence.

  8. Residual sum of squares - Wikipedia

    en.wikipedia.org/wiki/Residual_sum_of_squares

    The general regression model with n observations and k explanators, the first of which is a constant unit vector whose coefficient is the regression intercept, is = + where y is an n × 1 vector of dependent variable observations, each column of the n × k matrix X is a vector of observations on one of the k explanators, is a k × 1 vector of true coefficients, and e is an n× 1 vector of the ...

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