  When data do not conform to the hypothesis of a known sampling-variance, the
fitting of a constant to the set of measured values is a long debated problem.
Given the data, the fitting would require to find which measurand value is most
probable. A fitting procedure is here reviewed which assigns probabilities to
the possible measurand values, on the assumption that the uncertainty
associated with each datum is the lower bound to the standard deviation. This
procedure is applied to derive an estimate of the Planck constant.
