  Monte Carlo computer simulations are virtually the only way to analyze the
thermodynamic behavior of a system in a precise way. However, the various
existing methods exhibit extreme differences in their efficiency, depending on
model details and relevant questions. The original standard method, Metropolis
Monte Carlo, which provides only reliable statistical information at a given
(not too low) temperature has meanwhile been replaced by more sophisticated
methods which are typically far more efficient (the differences in time scales
can be compared with the age of the universe). However, none of the methods
yields automatically accurate results, i.e., a system-specific adaptation and
control is always needed. Thus, as in any good experiment, the most important
part of the data analysis is statistical error estimation.
