Introduction to imprecise probability and IP-based statistical methods

This lecture will introduce basic ideas of imprecise probability (IP), generalizing the classical (precise) theory of probability as a tool for uncertainty quantification. IP will be motivated from several perspectives, including practical aspects like limited or conflicting information and decision support. Some main advances in the field will be highlighted, together with the many challenges remaining. Some statistical methods based on IP will be introduced with examples to illustrate advantages.