It has also been shown that this bias comes from the linearization performed in the usual covariance propagation. This means that, even though the use of the covariance matrix can be very useful in analysing the data in a compact way using available computer algorithms, care is required if there is one large normalization uncertainty which affects all the data.

The effect discussed above has also been observed independently by R.W. Peelle and reported the year after the analysis of the CELLO data[48]. The problem has been extensively discussed among the community of nuclear physicists, where it is currently known as ``Peelle's Pertinent Puzzle''[50].

Recent cases in High Energy Physics in which this effect has been found to have biased the result are discussed in Refs. [51,52].

**Note added**: the solution outlined here is taken
from Ref. [47], and it has to be considered an *ad hoc*
solution. The general (of course Bayesian) solution
to the paradox has been worked out
recently[53], and it will
be published in a forthcoming paper.