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Añadir al carritoTaschenbuch. Condición: Neu. Applied Probability: Concepts and Applications of Random Variables | Random Variables | Adel Settati (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208429928 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Applied probability is a significant area of mathematics that connects theoretical probability concepts with their practical applications across various disciplines. It uses mathematical tools and frameworks to model, analyze, and interpret random phenomena. Central to applied probability are the concepts of random variables, representing outcomes of stochastic systems. These variables can be discrete, representing countable outcomes, or continuous, representing outcomes within a range, and their associated probability distributions provide a detailed description of the likelihood of different outcomes. Key topics in this field include probability measures, expectation, variance, higher-order moments, and the relationships between random variables through concepts such as covariance and correlation. These tools enable the quantification of uncertainty and variability, making applied probability essential for decision-making in situations with incomplete or uncertain information. Applications of applied probability extend across multiple disciplines. In engineering, it supports signal processing, network reliability, and system optimization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Applied probability is a significant area of mathematics that connects theoretical probability concepts with their practical applications across various disciplines. It uses mathematical tools and frameworks to model, analyze, and interpret random phenomena. Central to applied probability are the concepts of random variables, representing outcomes of stochastic systems. These variables can be discrete, representing countable outcomes, or continuous, representing outcomes within a range, and their associated probability distributions provide a detailed description of the likelihood of different outcomes. Key topics in this field include probability measures, expectation, variance, higher-order moments, and the relationships between random variables through concepts such as covariance and correlation. These tools enable the quantification of uncertainty and variability, making applied probability essential for decision-making in situations with incomplete or uncertain information. Applications of applied probability extend across multiple disciplines. In engineering, it supports signal processing, network reliability, and system optimization.