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| author | Raymond Hettinger <rhettinger@users.noreply.github.com> | 2019-03-01 05:47:26 (GMT) |
|---|---|---|
| committer | Miss Islington (bot) <31488909+miss-islington@users.noreply.github.com> | 2019-03-01 05:47:26 (GMT) |
| commit | 9add4b3317629933d88cf206a24b15e922fa8941 (patch) | |
| tree | 15bebdf56ab076c1cd0316dd05e230c646abbd9f /Doc | |
| parent | f684d83d86e1990784816d4b243d724e6ab8304f (diff) | |
| download | cpython-9add4b3317629933d88cf206a24b15e922fa8941.zip cpython-9add4b3317629933d88cf206a24b15e922fa8941.tar.gz cpython-9add4b3317629933d88cf206a24b15e922fa8941.tar.bz2 | |
bpo-36018: Add documentation link to "random variable" (GH-12114)
https://bugs.python.org/issue36018
Diffstat (limited to 'Doc')
| -rw-r--r-- | Doc/library/statistics.rst | 12 |
1 files changed, 7 insertions, 5 deletions
diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst index 8d961b7..8f8c009 100644 --- a/Doc/library/statistics.rst +++ b/Doc/library/statistics.rst @@ -471,9 +471,11 @@ A single exception is defined: :class:`NormalDist` objects =========================== -A :class:`NormalDist` is a a composite class that treats the mean and standard -deviation of data measurements as a single entity. It is a tool for creating -and manipulating normal distributions of a random variable. +:class:`NormalDist` is a tool for creating and manipulating normal +distributions of a `random variable +<http://www.stat.yale.edu/Courses/1997-98/101/ranvar.htm>`_. It is a +composite class that treats the mean and standard deviation of data +measurements as a single entity. Normal distributions arise from the `Central Limit Theorem <https://en.wikipedia.org/wiki/Central_limit_theorem>`_ and have a wide range @@ -530,7 +532,7 @@ of applications in statistics, including simulations and hypothesis testing. Using a `probability density function (pdf) <https://en.wikipedia.org/wiki/Probability_density_function>`_, - compute the relative likelihood that a random sample *X* will be near + compute the relative likelihood that a random variable *X* will be near the given value *x*. Mathematically, it is the ratio ``P(x <= X < x+dx) / dx``. @@ -544,7 +546,7 @@ of applications in statistics, including simulations and hypothesis testing. Using a `cumulative distribution function (cdf) <https://en.wikipedia.org/wiki/Cumulative_distribution_function>`_, - compute the probability that a random sample *X* will be less than or + compute the probability that a random variable *X* will be less than or equal to *x*. Mathematically, it is written ``P(X <= x)``. Instances of :class:`NormalDist` support addition, subtraction, |