Measure

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Measure is a mathematical concept that generalizes the everyday notion of size. Intuitively one can think of measure as length, weight, volume, distance from a point, probability, etc.

Consider a non-empty set \fs4 \Omega. Also consider a \fs4 \sigma-algebra on \fs4 \Omega, denoted with \fs4 \mathscr{F}. The pair \fs4 (\Omega, \mathscr{F}) is called a measure space, since we can apply the measure function on the members of \fs4 \mathscr{F}. The members of \fs4 \mathscr{F} are called just measurable.

Contrary to intuition, not all subsets of \fs4 \Omega are (necessarily) measurable, and therefore there are subsets that don't belong in any \fs4 \sigma-algebra \fs4 \mathscr{F}. An important example of such subsets is the Vitali set.

A measure \fs4 \mu will be a function

\fs4 \mu : \mathscr{F} \rightarrow [0, +\infty]

which satisfies the following properties:

  • The empty set has measure zero
\fs4 \mu(\emptyset) = 0
  • The measure of a countable union of disjoint sets equals the sum of their measures. If \fs4 F_1, F_2, \ldots \in \mathscr{F} with \fs4 F_i \cap F_j = \emptyset for \fs4 i \neq j, then
\fs4 \mu(\cup_{i=1}^\infty F_i) = \sum_{i=1}^\infty \mu(F_i)

We are particularly interested in measures that have the extra property that the total measure of \fs4 \Omega is one

\fs4 \mu(\Omega) = 1

If we look at the members of \fs4 \mathscr{F} as events then we can view this measure as the probability of these events, and therefore we call this measure a probability measure. Equipped with this probability measure, the measure space is called a probability space.


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