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  2. Confidence and prediction bands - Wikipedia

    en.wikipedia.org/wiki/Confidence_and_prediction...

    Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.

  3. FiveThirtyEight - Wikipedia

    en.wikipedia.org/wiki/FiveThirtyEight

    The final prediction by FiveThirtyEight on the morning of election day (November 8, 2016) had Hillary Clinton with a 71% chance to win the 2016 United States presidential election, [69] while other major forecasters had predicted Clinton to win with at least an 85% to 99% probability.

  4. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.

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  6. Accuracy paradox - Wikipedia

    en.wikipedia.org/wiki/Accuracy_paradox

    Even though the accuracy is ⁠ 10 + 999000 / 1000000 ⁠ ≈ 99.9%, 990 out of the 1000 positive predictions are incorrect. The precision of ⁠ 10 / 10 + 990 ⁠ = 1% reveals its poor performance. As the classes are so unbalanced, a better metric is the F1 score = ⁠ 2 × 0.01 × 1 / 0.01 + 1 ⁠ ≈ 2% (the recall being ⁠ 10 + 0 / 10 ...

  7. Nate Silver - Wikipedia

    en.wikipedia.org/wiki/Nate_Silver

    Their final prediction on November 8, 2016, gave Clinton a 71% chance to win the 2016 United States presidential election, [89] while other major forecasters had predicted Clinton to win with at least an 85% to 99% probability.

  8. Tolerance interval - Wikipedia

    en.wikipedia.org/wiki/Tolerance_interval

    A tolerance interval (TI) is a statistical interval within which, with some confidence level, a specified sampled proportion of a population falls. "More specifically, a 100×p%/100×(1−α) tolerance interval provides limits within which at least a certain proportion (p) of the population falls with a given level of confidence (1−α)."

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