Axiom:Kolmogorov Axioms
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Definition
Let $\EE$ be an experiment.
Let $\struct {\Omega, \Sigma, \Pr}$ be a probability measure on $\EE$.
Then $\EE$ can be defined as being a measure space $\struct {\Omega, \Sigma, \Pr}$, such that $\map \Pr \Omega = 1$.
Thus $\Pr$ satisfies the Kolmogorov axioms:
Axioms
\((1)\) | $:$ | \(\ds \forall A \in \Sigma:\) | \(\ds 0 \) | \(\ds \le \) | \(\ds \map \Pr A \le 1 \) | The probability of an event occurring is a real number between $0$ and $1$ | |||
\((2)\) | $:$ | \(\ds \map \Pr \Omega \) | \(\ds = \) | \(\ds 1 \) | The probability of some elementary event occurring in the sample space is $1$ | ||||
\((3)\) | $:$ | \(\ds \map \Pr {\bigcup_{i \mathop \ge 1} A_i} \) | \(\ds = \) | \(\ds \sum_{i \mathop \ge 1} \map \Pr {A_i} \) | where $\set {A_1, A_2, \ldots}$ is a countable (possibly countably infinite) set of pairwise disjoint events | ||||
That is, 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 |
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
- Definition:Measure Space: the Kolmogorov axioms follow directly from the fact that $\struct {\Omega, \Sigma, \Pr}$ is an example of such.
Source of Name
This entry was named for Andrey Nikolaevich Kolmogorov.
Sources
- 1986: Geoffrey Grimmett and Dominic Welsh: Probability: An Introduction ... (previous) ... (next): $1$: Events and probabilities: $1.3$: Probabilities