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  2. Probability axioms - Wikipedia

    en.wikipedia.org/wiki/Probability_axioms

    The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. [1] These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases. [2]

  3. Wald's equation - Wikipedia

    en.wikipedia.org/wiki/Wald's_equation

    Wald's equation. In probability theory, Wald's equation, Wald's identity[1] or Wald's lemma[2] is an important identity that simplifies the calculation of the expected value of the sum of a random number of random quantities. In its simplest form, it relates the expectation of a sum of randomly many finite-mean, independent and identically ...

  4. 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] where, for any , if , then these terms are simply omitted from the summation since is finite.

  5. 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 ...

  6. Law of the unconscious statistician - Wikipedia

    en.wikipedia.org/wiki/Law_of_the_unconscious...

    In probability theory and statistics, the law of the unconscious statistician, or LOTUS, is a theorem which expresses the expected value of a function g(X) of a random variable X in terms of g and the probability distribution of X. The form of the law depends on the type of random variable X in question. If the distribution of X is discrete and ...

  7. Conditional probability - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability

    t. e. In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) is already known to have occurred. [1] This particular method relies on event A occurring with some sort of relationship with another event B.

  8. Outline of probability - Wikipedia

    en.wikipedia.org/wiki/Outline_of_probability

    v. t. e. Probability is a measure of the likeliness that an event will occur. Probability is used to quantify an attitude of mind towards some proposition whose truth is not certain. The proposition of interest is usually of the form "A specific event will occur." The attitude of mind is of the form "How certain is it that the event will occur?"

  9. Lindeberg's condition - Wikipedia

    en.wikipedia.org/wiki/Lindeberg's_condition

    Lindeberg's condition. In probability theory, Lindeberg's condition is a sufficient condition (and under certain conditions also a necessary condition) for the central limit theorem (CLT) to hold for a sequence of independent random variables. [1][2][3] Unlike the classical CLT, which requires that the random variables in question have finite ...

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