Hello,
I have setup a toyMC that works in the following way:
 * on generic MC I make the mes histograms in bins of MX for B0-SS, B0-OS
and Bch
 * each bin of these histograms is randomized in a poisson way, i.e. it is
replaced by the output of a poisson randomizer with mean the original
value in the bin.
 * the fit is performed again.


I did 317 such tests (not that any failed, the loop command was a bit
idiot and can only give 317...). The distribution of the outcome (true
mean  value BrBr=0.0118) is in
http://www.slac.stanford.edu/~rfaccini/phys/vub/toyDist.eps
You can see that the statistical error is the same as in data

The pull distribution (BrBr-0.0118)/sigma(BrBr) is shown in
http://www.slac.stanford.edu/~rfaccini/phys/vub/toyPull.eps
where you can see that the error is 1.00+/-0.04, i.e. we can rule out that
we made other mistakes with the error in the fitting phase at the
4% level.

There is a bias which is 20% of the error (i.e. 5% relative), but I do not
know if we want to quote it as systematics: I am not throwing again the
selection, so the sample is biassed from the beginning, I would not trust
the shift
	ciao
	ric