The main focus of this tutorial/review is on presenting Prospect Theory in the context of the still ongoing debate between the behavioral (mainly descriptive) and the classical (mainly normative) approach in decision theory under risk and uncertainty. The goal is to discuss Prospect Theory vs. Expected Utility in a comparative way. We discuss: a) which assumptions (implicit and explicit) of the classical theory are being questioned in Prospect Theory; b) how does the theory incorporate robust experimental evidence, striving, at the same time, to find the right balance between the basic rationality postulates of Expected Utility (e.g. monotonicity wrt. First-Order Stochastic Dominance), psychological plausibility and mathematical elegance; c) how are risk attitudes modeled in the theory. In particular we discuss prospect stochastic dominance and the three-pillar structure of modeling risk attitudes in Prospect Theory involving: the non-additive decision weights with lower and upper subadditivity and their relationship to the notions of pessimism and optimism, as well as preferences towards consequences separated into preferences within and across the domains of gains and losses (corresponding to basic utility and loss aversion), d) example applications of Prospect Theory.