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  2. File:High School Probability and Statistics (Basic).pdf

    en.wikipedia.org/wiki/File:High_School...

    File:High_School_Probability_and_Statistics_(Advanced).pdf Licensing This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.

  3. Continuity correction - Wikipedia

    en.wikipedia.org/wiki/Continuity_correction

    Download as PDF; Printable version; ... Probability and Statistics for Engineering and the Sciences, Fourth Edition, Duxbury Press, 1995.

  4. 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.

  5. Ars Conjectandi - Wikipedia

    en.wikipedia.org/wiki/Ars_Conjectandi

    A History of Probability and Statistics and Their Applications before 1750. John Wiley & Sons. ISBN 978-0-471-72517-6. Maĭstrov, Leonid (1974), Probability Theory: A Historical Sketch, Academic Press; Maseres, Francis; Bernoulli, Jakob; Wallis, John (1798), The Doctrine of Permutations and Combinations, British Critic

  6. 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 .

  7. 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 ...

  8. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈ w aɪ b ʊ l / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.

  9. Multivariate random variable - Wikipedia

    en.wikipedia.org/wiki/Multivariate_random_variable

    Formally, a multivariate random variable is a column vector = (, …,) (or its transpose, which is a row vector) whose components are random variables on the probability space (,,), where is the sample space, is the sigma-algebra (the collection of all events), and is the probability measure (a function returning each event's probability).

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