A measure space is a basic object of measure theory, a branch of mathematics that studies generalized notions of volumes. It contains an underlying set, the subsets of this set that are feasible for measuring (the σ-algebra) and the method that is used for measuring (the measure). One important example of a measure space is a probability space.
A measurable space consists of the first two components without a specific measure.
A measure space is a triple where
is a set
is a σ-algebra on the set
is a measure on
In other words, a measure space consists of a measurable space together with a measure on it.
Set . The -algebra on finite sets such as the one above is usually the power set, which is the set of all subsets (of a given set) and is denoted by Sticking with this convention, we set
In this simple case, the power set can be written down explicitly:
As the measure, define by
so (by additivity of measures) and (by definition of measures).
This leads to the measure space It is a probability space, since The measure corresponds to the Bernoulli distribution with which is for example used to model a fair coin flip.
Most important classes of measure spaces are defined by the properties of their associated measures. This includes
Probability spaces, a measure space where the measure is a probability measure
Finite measure spaces, where the measure is a finite measure
finite measure spaces, where the measure is a -finite measure
Another class of measure spaces are the complete measure spaces.
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The course is based on Durrett's text book
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It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.
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