variance indicates that the data is spread out; a small variance indicates
it is clustered closely around the mean.
- If the optional second argument *mu* is given, it is typically the mean of
- the *data*. It can also be used to compute the second moment around a
- point that is not the mean. If it is missing or ``None`` (the default),
+ If the optional second argument *mu* is given, it should be the *population*
+ mean of the *data*. It can also be used to compute the second moment around
+ a point that is not the mean. If it is missing or ``None`` (the default),
the arithmetic mean is automatically calculated.
Use this function to calculate the variance from the entire population. To
the data is spread out; a small variance indicates it is clustered closely
around the mean.
- If the optional second argument *xbar* is given, it should be the mean of
- *data*. If it is missing or ``None`` (the default), the mean is
+ If the optional second argument *xbar* is given, it should be the *sample*
+ mean of *data*. If it is missing or ``None`` (the default), the mean is
automatically calculated.
Use this function when your data is a sample from a population. To calculate
>>> variance(data)
1.3720238095238095
- If you have already calculated the mean of your data, you can pass it as the
- optional second argument *xbar* to avoid recalculation:
+ If you have already calculated the sample mean of your data, you can pass it
+ as the optional second argument *xbar* to avoid recalculation:
.. doctest::