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author | Raymond Hettinger <rhettinger@users.noreply.github.com> | 2023-09-30 04:18:12 (GMT) |
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committer | GitHub <noreply@github.com> | 2023-09-30 04:18:12 (GMT) |
commit | 613c0d4e866341e15a66704643a6392ce49058ba (patch) | |
tree | 4fbf09b835c1fb4cc93304d0d95ed7fea1c4331a /Doc | |
parent | 14098b78f7453adbd40c53e32c29588611b7c87b (diff) | |
download | cpython-613c0d4e866341e15a66704643a6392ce49058ba.zip cpython-613c0d4e866341e15a66704643a6392ce49058ba.tar.gz cpython-613c0d4e866341e15a66704643a6392ce49058ba.tar.bz2 |
Add example for linear_regression() with proportional=True. (gh-110133)
Diffstat (limited to 'Doc')
-rw-r--r-- | Doc/library/statistics.rst | 19 |
1 files changed, 19 insertions, 0 deletions
diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst index a8a7901..f3c1bf2 100644 --- a/Doc/library/statistics.rst +++ b/Doc/library/statistics.rst @@ -14,6 +14,7 @@ .. testsetup:: * from statistics import * + import math __name__ = '<doctest>' -------------- @@ -741,6 +742,24 @@ However, for reading convenience, most of the examples show sorted sequences. *y = slope \* x + noise* + Continuing the example from :func:`correlation`, we look to see + how well a model based on major planets can predict the orbital + distances for dwarf planets: + + .. doctest:: + + >>> model = linear_regression(period_squared, dist_cubed, proportional=True) + >>> slope = model.slope + + >>> # Dwarf planets: Pluto, Eris, Makemake, Haumea, Ceres + >>> orbital_periods = [90_560, 204_199, 111_845, 103_410, 1_680] # days + >>> predicted_dist = [math.cbrt(slope * (p * p)) for p in orbital_periods] + >>> list(map(round, predicted_dist)) + [5912, 10166, 6806, 6459, 414] + + >>> [5_906, 10_152, 6_796, 6_450, 414] # actual distance in million km + [5906, 10152, 6796, 6450, 414] + .. versionadded:: 3.10 .. versionchanged:: 3.11 |