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Probability theory 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 probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space. Any specified subset of the sample space is called an event.Central subjects in probability theory include discrete and continuous random variables, probability distributions, and stochastic processes, which provide mathematical abstractions of non-deterministic or uncertain processes or measured quantities that may either be singl

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rdfs:label	Probability theory (en)
rdfs:comment	Probability theory 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 probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space. Any specified subset of the sample space is called an event.Central subjects in probability theory include discrete and continuous random variables, probability distributions, and stochastic processes, which provide mathematical abstractions of non-deterministic or uncertain processes or measured quantities that may either be singl (en)
sameAs	Probability theory Probability theory Probability theory
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Subject	Probability theory
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has abstract	Probability theory 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 probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space. Any specified subset of the sample space is called an event.Central subjects in probability theory include discrete and continuous random variables, probability distributions, and stochastic processes, which provide mathematical abstractions of non-deterministic or uncertain processes or measured quantities that may either be single occurrences or evolve over time in a random fashion.Although it is not possible to perfectly predict random events, much can be said about their behavior. Two major results in probability theory describing such behaviour are the law of large numbers and the central limit theorem. As a mathematical foundation for statistics, probability theory is essential to many human activities that involve quantitative analysis of data. Methods of probability theory also apply to descriptions of complex systems given only partial knowledge of their state, as in statistical mechanics or sequential estimation. A great discovery of twentieth-century physics was the probabilistic nature of physical phenomena at atomic scales, described in quantum mechanics. (en)
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is Wikipage redirect of	Probability/Theory Probability Theory Laws of probability Measure-theoretic probability theory Theory of Probability Theory of probabilities Theory of probability Mathematical probability Probability-theoretic ProbabilityTheory
is Link from a Wikipage to another Wikipage of	Fleming–Viot process Flemming Topsøe Florence Merlevède Fluid limit Fluid queue Fork–join queue Formal epistemology Formal science Foster's theorem Fourier analysis Fourier transform Fractional Brownian motion Francesca Biagini Francesco Paolo Cantelli Franck Barthe Frank Spitzer Greek letters used in mathematics, science, and engineering Greg Lawler List of statistical software List of statistics articles List of theorems List of unsolved problems in statistics Lists of mathematics topics Little's law Location–scale family Loewner differential equation Log-Laplace distribution Log-normal distribution Log probability Logarithm Logistic distribution Logit-normal distribution Machine learning Mad scientists of Stanisław Lem Magda Peligrad Marie Duflo Marina Ratner Marjorie Hahn Mark Freidlin Mark Pinsky Mark Semenovich Pinsker Non-Zero Probabilities Non-commutative conditional expectation Noncentral F-distribution Noncentral beta distribution Noncentral chi-squared distribution Noncentral chi distribution Nonlinear expectation Nonparametric skew Norm (mathematics) Normal-Wishart distribution Normal-exponential-gamma distribution Normal-gamma distribution Normal-inverse-Wishart distribution

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