  This paper describes a recent mathematical method called conflation for
consolidating data from independent experiments that are designed to measure
the same quantity, such as Planck's constant or the mass of the top quark.
Conflation is easy to calculate and visualize, and minimizes the maximum loss
in Shannon information in consolidating several independent distributions into
a single distribution. In order to benefit the experimentalist with a much more
transparent presentation than the previous mathematical treatise, the main
basic properties of conflation are derived in the special case of normal
(Gaussian) data. Included are examples of applications to real data from
measurements of the fundamental physical constants and from measurements in
high energy physics, and the conflation operation is generalized to weighted
conflation for situations when the underlying experiments are not uniformly
reliable.
