Abstract
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.
Connections
Explore this paper’s authors, topics and related work.
Building this map preview
BZPEER is loading the nearby papers, people, topics and institutions for this page.
Reviews 0
Write a review
No reviews yet.
Discussion 0
Add a comment
No comments yet.