On Fri, Dec 19, 2008 at 11:23, Sturla Molden <sturla@molden.no> wrote:
On 12/18/2008 12:02 PM, Robert Kern wrote:
The terms are commonly used in English the same way that you are using them. I just happen to disagree with the common practice.
I agree with this. Also:
"The problem is that the "unbiased" estimate for the standard deviation is *not* the square root of the "unbiased" estimate for the variance. The latter is what numpy.std(x, ddof=1) calculates, not the former."
An unbiased variance estimate is what people usually want. But 9 out of 10 practitioners think they need an unbiased standard deviation, and they think they get it from normalizing by N-1. They do the "right thing" just because their Stat 101 text tell them to, or because SPSS or MINITAB is doing it by default. Erroneous use of statistics due to mathematical incompetence is a major contribution to bad science.
Perhaps it is better if the docstring just specifies that ddof=1 normalizes by N-1, whereas ddof=0 normalizes by N?
How does the current version strike you? http://docs.scipy.org/numpy/docs/numpy.core.fromnumeric.std/ http://docs.scipy.org/numpy/docs/numpy.core.fromnumeric.var/ -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco