  In Quasi-Monte Carlo integration, the integration error is believed to be
generally smaller than in classical Monte Carlo with the same number of
integration points. Using an appropriate definition of an ensemble of
quasi-randompoint sets, we derive various results on the probability
distribution of the integration error, which can be compared to the standard
Central Limit theorem for normal stochastic sampling. In many cases, a Gaussian
error distribution is obtained.
