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Kolmogorov’s axioms define probability as a measure on events: non-negativity, normalization, and countable additivity.
Probability theory formalizes uncertainty using a sample space, events, and a probability measure that obeys clear axioms.
Probability quantifies uncertainty by assigning numbers between 0 and 1 to events in a sample space.