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. 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. 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... Thanks! Chris Barrington-Leigh UBC