This concept establishes the foundational axioms and operational laws governing stochastic events within the field of mathematical statistics and decision theory. It provides formal definitions for sample spaces, event intersections, unions, and complements to quantify uncertainty through precise numerical values known as probabilities. As a core submodule of elementary probability theory, it serves as the necessary theoretical substrate required before analyzing complex conditional relationships or Bayesian inference.
Prerequisite chain context: requires Outcome Definitions in Probability Theory.