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  2. Borel–Kolmogorov paradox - Wikipedia

    en.wikipedia.org/wiki/Borel–Kolmogorov_paradox

    The concept of a conditional probability with regard to an isolated hypothesis whose probability equals 0 is inadmissible. For we can obtain a probability distribution for [the latitude] on the meridian circle only if we regard this circle as an element of the decomposition of the entire spherical surface onto meridian circles with the given poles

  3. Chebyshev's inequality - Wikipedia

    en.wikipedia.org/wiki/Chebyshev's_inequality

    2.2 Measure-theoretic statement. 3 Example. ... Download as PDF; Printable version ... The one-sided variant can be used to prove the proposition that for probability ...

  4. Ionescu-Tulcea theorem - Wikipedia

    en.wikipedia.org/wiki/Ionescu-Tulcea_theorem

    In the mathematical theory of probability, the Ionescu-Tulcea theorem, sometimes called the Ionesco Tulcea extension theorem, deals with the existence of probability measures for probabilistic events consisting of a countably infinite number of individual probabilistic events.

  5. Event (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Event_(probability_theory)

    In probability theory, an event is a subset of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. [1] A single outcome may be an element of many different events, [2] and different events in an experiment are usually not equally likely, since they may include very different groups of outcomes. [3]

  6. Distribution function (measure theory) - Wikipedia

    en.wikipedia.org/wiki/Distribution_function...

    When the underlying measure on (, ()) is finite, the distribution function in Definition 3 differs slightly from the standard definition of the distribution function (in the sense of probability theory) as given by Definition 2 in that for the former, = while for the latter, () = = ().

  7. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    This is the same as saying that the probability of event {1,2,3,4,6} is 5/6. This event encompasses the possibility of any number except five being rolled. The mutually exclusive event {5} has a probability of 1/6, and the event {1,2,3,4,5,6} has a probability of 1, that is, absolute certainty.

  8. Kolmogorov extension theorem - Wikipedia

    en.wikipedia.org/wiki/Kolmogorov_extension_theorem

    The measure-theoretic approach to stochastic processes starts with a probability space and defines a stochastic process as a family of functions on this probability space. However, in many applications the starting point is really the finite-dimensional distributions of the stochastic process.

  9. Unit measure - Wikipedia

    en.wikipedia.org/wiki/Unit_measure

    The term measure here refers to the measure-theoretic approach to probability. Violations of unit measure have been reported in arguments about the outcomes of events [2] [3] under which events acquire "probabilities" that are not the probabilities of probability theory. In situations such as these the term "probability" serves as a false ...

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