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  2. Mathematical model - Wikipedia

    en.wikipedia.org/wiki/Mathematical_model

    Many everyday activities carried out without a thought are uses of mathematical models. A geographical map projection of a region of the earth onto a small, plane surface is a model which can be used for many purposes such as planning travel. [12]

  3. Information content - Wikipedia

    en.wikipedia.org/wiki/Information_content

    For example, if there is a one-in-a-million chance of Alice winning the lottery, her friend Bob will gain significantly more information from learning that she won than that she lost on a given day. (See also Lottery mathematics.) This establishes an implicit relationship between the self-information of a random variable and its variance.

  4. Outline of probability - Wikipedia

    en.wikipedia.org/wiki/Outline_of_probability

    The certainty that is adopted can be described in terms of a numerical measure, and this number, between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty) is called the probability. Probability theory is used extensively in statistics , mathematics , science and philosophy to draw conclusions about the likelihood of potential ...

  5. Dempster–Shafer theory - Wikipedia

    en.wikipedia.org/wiki/Dempster–Shafer_theory

    Arthur P. Dempster at the Workshop on Theory of Belief Functions (Brest, 1 April 2010).. The theory of belief functions, also referred to as evidence theory or Dempster–Shafer theory (DST), is a general framework for reasoning with uncertainty, with understood connections to other frameworks such as probability, possibility and imprecise probability theories.

  6. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    That is, the probability function f(x) lies between zero and one for every value of x in the sample space Ω, and the sum of f(x) over all values x in the sample space Ω is equal to 1. An event is defined as any subset of the sample space . The probability of the event is defined as

  7. Uncertainty quantification - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_quantification

    Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.

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