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1. 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. (Branch of mathematics concerning probability) [100%] 2023-10-10 [Probability theory]
2. Probability theory: 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. (Branch of mathematics concerning probability) [100%] 2024-01-04 [Probability theory]
3. Probability theory: A mathematical science in which the probabilities (cf. Probability) of certain random events are used to deduce the probabilities of other random events which are connected with the former events in some manner. (Mathematics) [100%] 2024-01-04
4. Uncorrelatedness (probability theory): In probability theory and statistics, two real-valued random variables, \displaystyle{ X }[/math], \displaystyle{ Y }[/math], are said to be uncorrelated if their covariance, \displaystyle{ \operatorname{cov}[X,Y] = \operatorname{E} - \operatorname{E} \operatorname{E} }[/math], is zero. If two ... (Probability theory) [81%] 2023-12-26 [Covariance and correlation]
5. Smoothness (probability theory): In probability theory and statistics, smoothness of a density function is a measure which determines how many times the density function can be differentiated, or equivalently the limiting behavior of distribution’s characteristic function. Formally, we call the distribution of ... (Probability theory) [81%] 2023-08-27 [Theory of probability distributions]
6. Martingale (probability theory): In probability theory, a martingale is a sequence of random variables (i.e., a stochastic process) for which, at a particular time, the conditional expectation of the next value in the sequence is equal to the present value, regardless of ... (Probability theory) [81%] 2022-08-07 [Stochastic processes] [Martingale theory]...
7. Contiguity (probability theory): In probability theory, two sequences of probability measures are said to be contiguous if asymptotically they share the same support. Thus the notion of contiguity extends the concept of absolute continuity to the sequences of measures. (Probability theory) [81%] 2023-12-02 [Probability theory]
8. Smoothness (probability theory): In probability theory and statistics, smoothness of a density function is a measure which determines how many times the density function can be differentiated, or equivalently the limiting behavior of distribution’s characteristic function. Formally, we call the distribution of ... (Probability theory) [81%] 2024-01-12 [Theory of probability distributions]
9. Filtration (probability theory): In the theory of stochastic processes, a subdiscipline of probability theory, filtrations are totally ordered collections of subsets that are used to model the information that is available at a given point and therefore play an important role in the ... (Probability theory) [81%] 2023-09-01 [Probability theory]
10. Copula (probability theory): In probability theory and statistics, a copula is a multivariate cumulative distribution function for which the marginal probability distribution of each variable is uniform on the interval [0, 1]. Copulas are used to describe/model the dependence (inter-correlation) between ... (Probability theory) [81%] 2024-03-21 [Actuarial science] [Multivariate statistics]...
11. Tree diagram (probability theory): In probability theory, a tree diagram may be used to represent a probability space. Tree diagrams may represent a series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck ... (Probability theory) [70%] 2023-09-03 [Experiment (probability theory)]
12. Bernstein inequalities (probability theory): In probability theory, Bernstein inequalities give bounds on the probability that the sum of random variables deviates from its mean. In the simplest case, let X1, ..., Xn be independent Bernoulli random variables taking values +1 and −1 with probability 1 ... (Probability theory) [70%] 2023-12-31 [Probabilistic inequalities]
13. Characteristic function (probability theory): In probability theory and statistics, the characteristic function of any real-valued random variable completely defines its probability distribution. If a random variable admits a probability density function, then the characteristic function is the Fourier transform (with sign reversal) of ... (Probability theory) [70%] 2024-01-04 [Functions related to probability distributions]
14. Boolean model (probability theory): For statistics in probability theory, the Boolean-Poisson model or simply Boolean model for a random subset of the plane (or higher dimensions, analogously) is one of the simplest and most tractable models in stochastic geometry. Take a Poisson point ... (Probability theory) [70%] 2023-09-16 [Spatial processes]
15. Quantum Logic and Probability Theory: Mathematically, quantum mechanics can be regarded as a non-classical probability calculus resting upon a non-classical propositional logic. More specifically, in quantum mechanics each probability-bearing proposition of the form “the value of physical quantity \(A\) lies in the ... (Philosophy) [63%] 2021-12-24
16. Method of moments (probability theory): In probability theory, the method of moments is a way of proving convergence in distribution by proving convergence of a sequence of moment sequences. Suppose X is a random variable and that all of the moments exist. (Probability theory) [63%] 2023-02-08 [Moment (mathematics)]
17. Chebyshev inequality in probability theory: Bienaymé–Chebyshev inequality An inequality in probability theory that gives a bound on the probability of deviation of a given random variable from its mathematical expectation in terms of its variance. Let $ X ( \omega ) $ be a random variable with finite mathematical ... (Mathematics) [63%] 2024-01-04 [Distribution theory]
18. Probability Theory and Related Fields: Probability Theory and Related Fields is a peer-reviewed mathematics journal published by Springer. Established in 1962, it was originally named Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, with the English replacing the German starting from volume 71 (1986). [63%] 2024-01-04 [Probability journals] [Academic journals established in 1962]...
19. Moments, method of (in probability theory): A method for determining a probability distribution by its moments (cf. Moment). (Mathematics) [57%] 2024-01-12
20. Catalog of articles in probability theory: This page lists articles related to probability theory. In particular, it lists many articles corresponding to specific probability distributions. [57%] 2023-11-04 [Statistics-related lists] [Mathematics-related lists]...
21. Principles of the Theory of Probability: Principles of the Theory of Probability is a 1939 book about probability by the philosopher Ernest Nagel. It is considered a classic discussion of its subject. (Philosophy) [57%] 2022-12-08 [Philosophy books]
22. Theory of Probability and Mathematical Statistics: Theory of Probability and Mathematical Statistics is a peer-reviewed international scientific journal published by Taras Shevchenko National University of Kyiv jointly with the American Mathematical Society two times per year in both print and electronic formats. The subjects covered ... [57%] 2023-09-09 [Statistics journals] [Probability journals]...
23. Principles of the Theory of Probability: Principles of the Theory of Probability is a 1939 book about probability by the philosopher Ernest Nagel. It is considered a classic discussion of its subject. (1939 book by Ernest Nagel) [57%] 2024-10-17 [Books about philosophy of mathematics]
24. Gnedenko, A course in the theory of probability: A course in the theory of probability (Курс теории вероятностей) is a book in probability theory by Boris Vladimirovich Gnedenko, originally in Russian (1950). The book has gone through six Russian editions and has been translated into English, German, Polish and Arabic. (Mathematics) [50%] 2023-10-25
25. Feller, An introduction to probability theory and its applications: An introduction to probability theory and its applications is a two-volume book in probability theory by William Feller. The book has been reprinted several times and translated into Russian. (Mathematics) [47%] 2023-10-13