Axiom:Kolmogorov Axioms

Definition
Let $\mathcal E$ be an experiment.

Let $\struct {\Omega, \Sigma, \Pr}$ be a probability measure on $\mathcal E$.

Then $\mathcal E$ can be defined as being a measure space $\struct {\Omega, \Sigma, \Pr}$, such that $\map \Pr \Omega = 1$.

Thus $\Pr$ satisfies the Kolmogorov axioms:

First Axiom

 * $\forall A \in \Sigma: 0 \le \map \Pr A \le 1$

The probability of an event occurring is a real number between $0$ and $1$.

Second Axiom

 * $\map \Pr \Omega = 1$

The probability of some elementary event occurring in the sample space is $1$.

Third Axiom
Let $A_1, A_2, \ldots$ be a countable (possibly countably infinite) sequence of pairwise disjoint events.

Then:
 * $\displaystyle \map \Pr {\bigcup_{i \mathop \ge 1} A_i} = \sum_{i \mathop \ge 1} \map \Pr {A_i}$

The probability of any one of countably many pairwise disjoint events occurring is the sum of the probabilities of the occurrence of each of the individual events.

As an elementary and easily-digested consequence of this, we have:


 * $\forall A, B \in \Sigma: A \cap B = \O \implies \map \Pr {A \cup B} = \map \Pr A + \map \Pr B$

Also defined as
Some sources include:
 * $\map \Pr \O = 0$

but this is strictly speaking not axiomatic as it can be deduced from the other axioms.

Also see

 * Elementary Properties of Probability Measure


 * Definition:Measure Space: the Kolmogorov axioms follow directly from the fact that $\struct {\Omega, \Sigma, \Pr}$ is an example of such.