There are many situations in which parametric statistical techniques a
re less than ideal for evaluating a simulated system. For most simulat
ion output, one must rely heavily on the central limit theorem in orde
r to apply parametric statistical techniques. The bootstrap statistic
is a nonparametric sample-resample technique that makes no distributio
nal assumptions and may be used for estimation and hypothesis testing.
The authors propose the bootstrap as a valuable tool for the analysis
of simulation output data since it can be used in situations in which
either the distribution is not known or normal approximations are ina
ppropriate. Furthermore, since bootstrapping is itself a simulation te
chnique it is inherently satisfying as a tool for the analysis of simu
lation output data. Illustrations are presented.