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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] There are several other (equivalent) approaches to formalising ...

  3. Bernoulli trial - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_trial

    Graphs of probability P of not observing independent events each of probability p after n Bernoulli trials vs np for various p.Three examples are shown: Blue curve: Throwing a 6-sided die 6 times gives a 33.5% chance that 6 (or any other given number) never turns up; it can be observed that as n increases, the probability of a 1/n-chance event never appearing after n tries rapidly converges to ...

  4. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    [I]n 1922, I proposed the term 'likelihood,' in view of the fact that, with respect to [the parameter], it is not a probability, and does not obey the laws of probability, while at the same time it bears to the problem of rational choice among the possible values of [the parameter] a relation similar to that which probability bears to the ...

  5. 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.

  6. 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 ...

  7. Measure-preserving dynamical system - Wikipedia

    en.wikipedia.org/wiki/Measure-preserving...

    Example of a (Lebesgue measure) preserving map: T : [0,1) → [0,1), Unlike the informal example above, the examples below are sufficiently well-defined and tractable that explicit, formal computations can be performed. μ could be the normalized angle measure dθ/2π on the unit circle, and T a rotation.

  8. Conditional expectation - Wikipedia

    en.wikipedia.org/wiki/Conditional_expectation

    In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated with respect to the conditional probability distribution. If the random variable can take on only a finite number of values, the "conditions" are that the variable can only take on a subset of ...

  9. Rotational invariance - Wikipedia

    en.wikipedia.org/wiki/Rotational_invariance

    In quantum mechanics, rotational invariance is the property that after a rotation the new system still obeys Schrödinger's equation. That is [please be gentle on the reader and define E and H] [,] = for any rotation R. Since the rotation does not depend explicitly on time, it commutes with the energy operator.