  We discuss a method to obtain the true event-by-event net-charge multiplicity
distributions from a corresponding measured distribution which is subjected to
detector effects such as finite particle counting efficiency. The approach is
based on the Bayes method for unfolding of distributions. We are able to
faithfully unfold back the measured distributions to match with their
corresponding true distributions obtained for a widely varying underlying
particle production mechanism, beam energy and collision centrality.
Particularly the mean, variance, skewness, kurtosis, their products and ratios
of net-charge distributions from the event generators are shown to be
successfully unfolded from the measured distributions constructed to mimic a
real experimental distribution. We demonstrate the necessity to account for
detector effects before associating the higher moments of net-charge
distributions with physical quantities or phenomena. The advantage of this
approach being that one need not construct new observable to cancel out
detector effects which loose their ability to be connected to physical
quantities calculable in standard theories.
