Re: interpretation of fit errors

[Bastian M. <bma...@we...>]

For what it's worth, here's the result of a little survey on data 
analysis packages:

* Minuit does not scale
* Origin offers both options, the default being version dependent
* SAS and Mathematica default to scaling of errors

The default choice of how to treat errors is somewhat arbitrary and 
depends on the problem at hand - I am not arguing about that. For a 
given problem only one choice is correct, though.

The default for gnuplot has been chosen long ago. All I am proposing is 
to make this default user changeable. Actual name suggestions for that 
setting are more than welcome!

IMHO there's no point in printing both numbers and even creating another 
error variable. As pointed out earlier, the other value can still be 
easily obtained by multiplying/dividing by the variable FIT_STDFIT.

Finally, here's an example of why _not_ to scale fit errors in 
combination with "real" data errors is important:

Consider NDF = 10. According to the ChiSq distribution, ChiSq = 6.74 
corresponds to P = 0.75, with STDFIT = 0.82, whereas and ChiSq = 12.55 
corresponds to P = 0.25, with STDFIT = 1.12. It is equally probable to 
obtain either ChiSq value, but scaling would tells us errors should 
differ by 30%!

In physics a probability P of the fit below 0.05 or above 0.95 is 
typically considered as an indication of "something being wrong", ie. 
there's some problem with data, errors or model. But within that range 
the fit is accepted. For NDF=10, Bernhard's example of STDFIT=10 would 
correspond to P < 10^-200.

   Bastian