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| author | Łukasz Langa <lukasz@langa.pl> | 2022-06-21 19:37:09 (GMT) |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-06-21 19:37:09 (GMT) |
| commit | 38fdff9274835c008c1e6c0c6546c23139e77c0f (patch) | |
| tree | 0aabcb0a14cca6a47070e58deee4e87339f90984 /Doc/library/statistics.rst | |
| parent | 54250e73538cf498028f73b9c9a4905294def622 (diff) | |
| download | cpython-38fdff9274835c008c1e6c0c6546c23139e77c0f.zip cpython-38fdff9274835c008c1e6c0c6546c23139e77c0f.tar.gz cpython-38fdff9274835c008c1e6c0c6546c23139e77c0f.tar.bz2 | |
[3.10] gh-93851: Fix all broken links in Doc/ (GH-93853) (GH-94078)
(cherry picked from commit f62ff97f31a775cc7956adeae32c14e7c85bdc15)
Co-authored-by: Oleg Iarygin <oleg@arhadthedev.net>
Diffstat (limited to 'Doc/library/statistics.rst')
| -rw-r--r-- | Doc/library/statistics.rst | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst index fd48619..1f55ae8 100644 --- a/Doc/library/statistics.rst +++ b/Doc/library/statistics.rst @@ -771,7 +771,7 @@ of applications in statistics. Compute the inverse cumulative distribution function, also known as the `quantile function <https://en.wikipedia.org/wiki/Quantile_function>`_ or the `percent-point - <https://www.statisticshowto.datasciencecentral.com/inverse-distribution-function/>`_ + <https://web.archive.org/web/20190203145224/https://www.statisticshowto.datasciencecentral.com/inverse-distribution-function/>`_ function. Mathematically, it is written ``x : P(X <= x) = p``. Finds the value *x* of the random variable *X* such that the @@ -920,7 +920,7 @@ probability that the Python room will stay within its capacity limits? Normal distributions commonly arise in machine learning problems. Wikipedia has a `nice example of a Naive Bayesian Classifier -<https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Sex_classification>`_. +<https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Person_classification>`_. The challenge is to predict a person's gender from measurements of normally distributed features including height, weight, and foot size. |