This paper proposes a set-membership method to characterize a probabilistic set, i.e., a set enclosing the true value for the parameter vector of a parametric system with a given probability. The approach assumes that all errors are independent and an interval for the error is known. To each error interval, a probability to be an outlier is provided. It is shown that characterizing the probabilistic set is a set inversion problem. The main contribution of the paper is to provide a method to characterize the inner part of the probabilistic set. As an illustration, an application to the static localization of a mobile robot is considered.