  This paper introduces and reviews some of the principles and methods used in
Bayesian reliability. It specifically discusses methods used in the analysis of
success/no-success data and then reminds the reader of a simple Monte Carlo
algorithm that can be used to calculate the posterior distribution of a
system's reliability. This algorithm is especially useful when a system's
reliability is modeled through the reliability of its subcomponents, yet only
system-level data is available.
