On Thu, Sep 9, 2010 at 10:22 PM, cpblpublic <[email protected]> wrote: > > > I am looking for some reaally basic statistical tools. I have some > sample data, some sample weights for those measurements, and I want to > calculate a mean and a standard error of the mean. > > Here are obvious places to look: > > numpy > scipy.stats > statsmodels > > It seems to me that numpy's "mean" and "average" functions have their > names backwards. That is, often a mean is defined more generally than > average, and includes the possibility of weighting, but in this case > it is "average" that has a weights argument. Can these functions be > merged/renamed/deprecated in the future? It's clear to me that "mean" > should allow for weights.
I think of weighted mean and weighted average, pretty much as synonyms, changing names would break backwards compatibility without any real benefit, in my opinion. > > None of these modules, above, offer standard error of the mean which > incorporates weights. scipy.stats.sem() doesn't, and that's the closest > thing. numpy's "var" doesn't allow weights. > There aren't any weighted variances in the above modules. for weighted statistics, I usually refer to ticket 604 http://projects.scipy.org/scipy/attachment/ticket/604/Statistics.py but I didn't see weighted sem in it > > Again, are there favoured codes for these functions? Can they be > incorporated appropriately in the future? > > Most immediately, I'd love to get code for weighted sem. I'll write it > otherwise, but it might be crude and dumb... just a thought, I still have to check the details: Estimating statsmodels.WLS with just a constant should give all the result statistics on the mean, e.g. bse for variance of constant, t() for t-statistic Josef > > Thanks! > Chris Barrington-Leigh > UBC > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
