A measure of uncertainty over events, formalized as a function mapping outcomes to values in [0, 1].
axioms:: Kolmogorov's axioms ground probability in set theory and measure theory
Bayes theorem inverts conditional probabilities, enabling inference from evidence
distributions (normal, Poisson, exponential) characterize random variables
stochastic processes (Markov chains, Brownian motion) model evolution over time
law of large numbers and central limit theorem bridge probability to statistics
entropy connects probability to information theory and thermodynamics
Foundation of machine learning, game theory, quantum mechanics, and optimization
Related:: combinatorics, calculus, differential equations