Classical probability theory and mathematical statistics appear
sometimes too rigid for real life problems, especially while dealing
with vague data or imprecise requirements. These problems have motivated
many researchers to "soften" the classical theory. Some "softening"
approaches utilize concepts and techniques developed in theories such as
fuzzy sets theory, rough sets, possibility theory, theory of belief
functions and imprecise probabilities, etc. Since interesting
mathematical models and methods have been proposed in the frameworks of
various theories, this text brings together experts representing
different approaches used in soft probability, statistics and data
analysis.