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  2. Measurable space - Wikipedia

    en.wikipedia.org/wiki/Measurable_space

    The term Borel space is used for different types of measurable spaces. It can refer to any measurable space, so it is a synonym for a measurable space as defined above [1] a measurable space that is Borel isomorphic to a measurable subset of the real numbers (again with the Borel -algebra) [3]

  3. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    In probability theory, a probability space or a probability triple (,,) is a mathematical construct that provides a formal model of a random process or "experiment". For example, one can define a probability space which models the throwing of a die. A probability space consists of three elements: [1] [2]

  4. Measure space - Wikipedia

    en.wikipedia.org/wiki/Measure_space

    A measurable space consists of the first two components without a specific measure. Definition. A measure space is a triple ... It is a probability space, ...

  5. Measure (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Measure_(mathematics)

    Every probability space gives rise to a measure which takes the value 1 on the whole space (and therefore takes all its values in the unit interval [0, 1]). Such a measure is called a probability measure or distribution. See the list of probability distributions for instances.

  6. Standard probability space - Wikipedia

    en.wikipedia.org/wiki/Standard_probability_space

    A measurable subset of a standard probability space is a standard probability space. It is assumed that the set is not a null set, and is endowed with the conditional measure. See (Rokhlin 1952, Sect. 2.3 (p. 14)) and (Haezendonck 1973, Proposition 5). Every probability measure on a standard Borel space turns it into a standard probability space.

  7. Measurable function - Wikipedia

    en.wikipedia.org/wiki/Measurable_function

    In probability theory, a measurable function on a probability space is known as a random variable. Formal definition. Let (, ...

  8. Borel measure - Wikipedia

    en.wikipedia.org/wiki/Borel_measure

    Given a Borel measure μ on a metric space X such that μ(X) > 0 and μ(B(x, r)) ≤ r s holds for some constant s > 0 and for every ball B(x, r) in X, then the Hausdorff dimension dim Haus (X) ≥ s. A partial converse is provided by the Frostman lemma: [7] Lemma: Let A be a Borel subset of R n, and let s > 0. Then the following are equivalent:

  9. Probability measure - Wikipedia

    en.wikipedia.org/wiki/Probability_measure

    A probability measure mapping the σ-algebra for events to the unit interval.. The requirements for a set function to be a probability measure on a σ-algebra are that: . must return results in the unit interval [,], returning for the empty set and for the entire space.