On 2 April 2014 16:06, Sturla Molden <[email protected]> wrote:
> <[email protected]> wrote: > > > pandas came later and thought ddof=1 is worth more than consistency. > > Pandas is a data analysis package. NumPy is a numerical array package. > > I think ddof=1 is justified for Pandas, for consistency with statistical > software (SPSS et al.) > > For NumPy, there are many computational tasks where the Bessel correction > is not wanted, so providing a uncorrected result is the correct thing to > do. NumPy should be a low-level array library that does very little magic. All this discussion reminds me of the book "Numerical Recipes": "if the difference between N and N - 1 ever matters to you, then you are probably up to no good anyway -- e.g., trying to substantiate a questionable hypothesis with marginal data." For any reasonably sized data set, it is a correction in the second significant figure.
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