  The statistical procedure used in the search for the Higgs boson is
investigated in this paper. A Bayesian hierarchical model is proposed that uses
the information provided by the theory in the analysis of the data generated by
the particle detectors. In addition, we develop a Bayesian decision making
procedure that combines the two steps of the current method (discovery and
exclusion) into one and can be calibrated to satisfy frequency theory error
rate requirements. .
