Merge pull request #16878 from davidedalbosco/patch-1

DOC: edit to the documentation of lib/polynomial.py/polyfit

1 files changed, 6 insertions, 5 deletions

diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index 420ec245b..1c124cc0e 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -494,11 +494,12 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False):
     cov : bool or str, optional
         If given and not `False`, return not just the estimate but also its
         covariance matrix. By default, the covariance are scaled by
-        chi2/sqrt(N-dof), i.e., the weights are presumed to be unreliable
-        except in a relative sense and everything is scaled such that the
-        reduced chi2 is unity. This scaling is omitted if ``cov='unscaled'``,
-        as is relevant for the case that the weights are 1/sigma**2, with
-        sigma known to be a reliable estimate of the uncertainty.
+        chi2/dof, where dof = M - (deg + 1), i.e., the weights are presumed 
+        to be unreliable except in a relative sense and everything is scaled 
+        such that the reduced chi2 is unity. This scaling is omitted if 
+        ``cov='unscaled'``, as is relevant for the case that the weights are 
+        1/sigma**2, with sigma known to be a reliable estimate of the 
+        uncertainty.
 
     Returns
     -------