  Higher order correlation measurements involve multiple event averages which
must run over unequal events to avoid statistical bias. We derive correction
formulas for small event samples, where the bias is largest, and utilize the
results to achieve savings in CPU time consumption for the star integral.
Results from a simple model of correlations illustrate the utility and
importance of these corrections. Single-event correlation measurements such as
in galaxy distributions and envisaged at RHIC must take great care to avoid
this unnecessary pitfall.
