bpo-44151: Various grammar, word order, and markup fixes (GH-26344) (GH-26345)
diff --git a/Lib/statistics.py b/Lib/statistics.py
index f164210a..b1b6131 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -923,26 +923,26 @@ def correlation(x, y, /):
def linear_regression(x, y, /):
- """Intercept and slope for simple linear regression
+ """Slope and intercept for simple linear regression.
- Return the intercept and slope of simple linear regression
+ Return the slope and intercept of simple linear regression
parameters estimated using ordinary least squares. Simple linear
- regression describes relationship between *x* and
- *y* in terms of linear function:
+ regression describes relationship between an independent variable
+ *x* and a dependent variable *y* in terms of linear function:
- y = intercept + slope * x + noise
+ y = slope * x + intercept + noise
- where *intercept* and *slope* are the regression parameters that are
+ where *slope* and *intercept* are the regression parameters that are
estimated, and noise represents the variability of the data that was
not explained by the linear regression (it is equal to the
- difference between predicted and actual values of dependent
+ difference between predicted and actual values of the dependent
variable).
The parameters are returned as a named tuple.
>>> x = [1, 2, 3, 4, 5]
>>> noise = NormalDist().samples(5, seed=42)
- >>> y = [2 + 3 * x[i] + noise[i] for i in range(5)]
+ >>> y = [3 * x[i] + 2 + noise[i] for i in range(5)]
>>> linear_regression(x, y) #doctest: +ELLIPSIS
LinearRegression(slope=3.09078914170..., intercept=1.75684970486...)