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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