Measure, Measure Space, and Probability Measure
definitionAnalysisProbabilitydef:measure-measure-space-2026aLet be a \reftext{def:sigma-algebra-measurable-space-2026a}{measurable space}.
Write for the set , where is a formal symbol with the conventions for all , for all real , and . The \textbf{sum} of a \reftext{def:sequence-in-set-2026a}{sequence} in is defined as follows: if every is real and the partial sums are \reftext{def:upper-bound-supremum-c54-2026b}{bounded above}, then is their least upper bound (which is also their \reftext{def:limit-sequence-real-c54-2026a}{limit}, as the partial sums are nondecreasing); otherwise .
A \textbf{measure} on is a function such that and, for every sequence of pairwise disjoint members of ,
(\textbf{countable additivity}). The triple is a \textbf{measure space}.
The measure is \textbf{finite} if ; it is \textbf{-finite} if there is a sequence in with and for every ; and it is a \textbf{probability measure} if .
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