[SciPy-User] StdErr Problem with Gary Strangman's linregress function

totalbull@ma... totalbull@ma...
Sun Jan 10 15:35:35 CST 2010


Hello, Excel and scipy.stats.linregress are disagreeing on the standard error of a regression. 

I need to find the standard errors of a bunch of regressions, and prefer to use pure Python than RPy. So I am going to scipy.stats.linregress, as advised at:
http://www2.warwick.ac.uk/fac/sci/moac/currentstudents/peter_cock/python/lin_reg/#linregress

>>> from scipy import stats
>>> x = [5.05, 6.75, 3.21, 2.66]
>>> y = [1.65, 26.5, -5.93, 7.96]
>>> gradient, intercept, r_value, p_value, std_err = stats.linregress(x,y)
>>> gradient
5.3935773611970186
>>> intercept
-16.281127993087829
>>> r_value
0.72443514211849758
>>> r_value**2
0.52480627513624778
>>> std_err
3.6290901222878866


The problem is that the std error calculation does not agree with what is returned in Microsoft Excel's STEYX function (whereas all the other output does). From Excel:




Anybody knows what's going on? Any alternative way of getting the standard error without going to R?



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