https://github.com/python/cpython/commit/613c0d4e866341e15a66704643a6392ce49... commit: 613c0d4e866341e15a66704643a6392ce49058ba branch: main author: Raymond Hettinger <rhettinger@users.noreply.github.com> committer: rhettinger <rhettinger@users.noreply.github.com> date: 2023-09-29T23:18:12-05:00 summary: Add example for linear_regression() with proportional=True. (gh-110133) files: M Doc/library/statistics.rst diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst index a8a7901256532..f3c1bf20ae3ac 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