Commit 3798c61e by Theophile GENTILHOMME

### Math support for conf inter doc

parent 3a88f2c7
Pipeline #17794 passed with stage
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 ... @@ -208,18 +208,22 @@ Both functions require that at least one probe item exists, which has no accordi ... @@ -208,18 +208,22 @@ Both functions require that at least one probe item exists, which has no accordi Confidence interval Confidence interval ------------------- ------------------- A confidence interval for parameter x consists of a lower A confidence interval for parameter :math:x consists of a lower estimate L, and an upper estimate U, such that the probability of the true value being estimate :math:L, and an upper estimate :math:U, such that the probability within the interval estimate is equal to \alpha. For example, of the true value being within the interval estimate is equal to :math:\alpha. a 95% confidence interval (i.e. \alpha = 0.95) for a parameter x is given by [L, U] such that For example, a 95% confidence interval (i.e. :math:\alpha = 0.95) for a Prob(x∈[L,U]) = 95%. The smaller the test size, the wider the confidence parameter :math:x is given by :math:[L, U] such that interval will be, and the greater alpha, the smaller the confidence interval .. math:: Prob(x∈[L,U]) = 95% The smaller the test size, the wider the confidence interval will be, and the greater :math:\alpha, the smaller the confidence interval will be. will be. The Clopper-Pearson interval_, a common method for calculating The Clopper-Pearson interval_, a common method for calculating confidence intervals, is function of the number of success, the number of trials confidence intervals, is function of the number of success, the number of trials and confidence and confidence value \alpha is used as :py:func:bob.measure.utils.confidence_for_indicator_variable. value :math:\alpha is used as :py:func:bob.measure.utils.confidence_for_indicator_variable. It is based on the cumulative probabilities of the binomial distribution. This It is based on the cumulative probabilities of the binomial distribution. This method is quite conservative, meaning that the true coverage rate of a 95% method is quite conservative, meaning that the true coverage rate of a 95% Clopper–Pearson interval may be well above 95%. Clopper–Pearson interval may be well above 95%. ... ...
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