Definition:Probability Space
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Definition
A probability space is a measure space $\struct {\Omega, \Sigma, \Pr}$ in which $\map \Pr \Omega = 1$.
A probability space is used to define the parameters determining the outcome of an experiment $\EE$.
In this context, the elements of a probability space are generally referred to as follows:
- $\Omega$ is called the sample space of $\EE$
- $\Sigma$ is called the event space of $\EE$
- $\Pr$ is called the probability measure on $\EE$.
Thus it is a measurable space $\struct {\Omega, \Sigma}$ with a probability measure $\Pr$.
Discrete Probability Space
Let $\Omega$ be a discrete sample space.
Then $\left({\Omega, \Sigma, \Pr}\right)$ is known as a discrete probability space.
Continuous Probability Space
Let $\Omega$ be a continuum.
Then $\left({\Omega, \Sigma, \Pr}\right)$ is known as a continuous probability space.
Also see
- Results about probability theory can be found here.
Sources
- 1986: Geoffrey Grimmett and Dominic Welsh: Probability: An Introduction ... (previous) ... (next): $1$: Events and probabilities: $1.1$: Experiments with chance
- 1986: Geoffrey Grimmett and Dominic Welsh: Probability: An Introduction ... (previous) ... (next): $1$: Events and probabilities: $1.4$: Probability spaces
- 2005: René L. Schilling: Measures, Integrals and Martingales ... (previous) ... (next): $4.2$
- 2013: Donald L. Cohn: Measure Theory (2nd ed.) ... (previous) ... (next): $10.1$: Basics