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author | rgommers <ralf.gommers@googlemail.com> | 2010-06-02 13:07:10 +0000 |
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committer | rgommers <ralf.gommers@googlemail.com> | 2010-06-02 13:07:10 +0000 |
commit | 76e25d22ca216d8f30c74b8df79edd1d8ffdd242 (patch) | |
tree | 11e01eaa2f3a0962532d6b7728b7cbedb7fbc9da /numpy/core/fromnumeric.py | |
parent | e7c87d78cb3a6a3cb24276a5cf3fdb3f4d0bc43c (diff) | |
download | numpy-76e25d22ca216d8f30c74b8df79edd1d8ffdd242.tar.gz |
DOC: merge wiki edits for module core.
Diffstat (limited to 'numpy/core/fromnumeric.py')
-rw-r--r-- | numpy/core/fromnumeric.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index b255e89af..c142cd1ed 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -2371,7 +2371,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0): The standard deviation is the square root of the average of the squared deviations from the mean, i.e., ``std = sqrt(mean(abs(x - x.mean())**2))``. - The mean is normally calculated as ``x.sum() / N``, where + The average squared deviation is normally calculated as ``x.sum() / N``, where ``N = len(x)``. If, however, `ddof` is specified, the divisor ``N - ddof`` is used instead. In standard statistical practice, ``ddof=1`` provides an unbiased estimator of the variance of the infinite population. ``ddof=0`` |