  Given a stream of Bernoulli random variables, consider the problem of
estimating the mean of the random variable within a specified relative error
with a specified probability of failure. Until now, the Gamma Bernoulli
Approximation Scheme (GBAS) was the method that accomplished this goal using
the smallest number of average samples. In this work, a new method is
introduced that is faster when the mean is bounded away from zero. The process
uses a two-stage process together with some simple inequalities to get rigorous
bounds on the error probability.
