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  2. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    v. t. e. The probabilities of rolling several numbers using two dice. Probability is the branch of mathematics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1][1][2] A simple example is ...

  3. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms. Typically these axioms formalise probability in terms of a ...

  4. Bayes' theorem - Wikipedia

    en.wikipedia.org/wiki/Bayes'_theorem

    Bayes' theorem (alternatively Bayes' law or Bayes' rule, after Thomas Bayes) gives a mathematical rule for inverting conditional probabilities, allowing us to find the probability of a cause given its effect. [1] For example, if the risk of developing health problems is known to increase with age, Bayes' theorem allows the risk to an individual ...

  5. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    t. e. In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1][2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]

  6. Law of total probability - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_probability

    The law of total probability is [1] a theorem that states, in its discrete case, if is a finite or countably infinite set of mutually exclusive and collectively exhaustive events, then for any event. or, alternatively, [1] {\displaystyle P (A)=\sum _ {n}P (A\mid B_ {n})P (B_ {n}),} where, for any , if , then these terms are simply omitted from ...

  7. Probability axioms - Wikipedia

    en.wikipedia.org/wiki/Probability_axioms

    The probability of an event is a non-negative real number: R ≥ 0 ∀ {\displaystyle P (E)\in \mathbb {R} ,P (E)\geq 0\qquad \forall E\in F} where is the event space. It follows (when combined with the second axiom) that is always finite, in contrast with more general measure theory. Theories which assign negative probability relax the first ...

  8. Probability interpretations - Wikipedia

    en.wikipedia.org/wiki/Probability_interpretations

    There are two broad categories [1][2] of probability interpretations which can be called "physical" and "evidential" probabilities. Physical probabilities, which are also called objective or frequency probabilities, are associated with random physical systems such as roulette wheels, rolling dice and radioactive atoms.

  9. Problem of points - Wikipedia

    en.wikipedia.org/wiki/Problem_of_points

    Problem of points. The problem of points, also called the problem of division of the stakes, is a classical problem in probability theory. One of the famous problems that motivated the beginnings of modern probability theory in the 17th century, it led Blaise Pascal to the first explicit reasoning about what today is known as an expected value.

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