ISBN: 9781461460398 - strategic economic decision-making: using bayesian belief networks to solve complex problems: 9 (springerbriefs in statistics) (10 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2012

    1461460395 / 9781461460398

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    Editorial: Springer, 2012

    1461460395 / 9781461460398

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    Editorial: Springer, 2012

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    Paperback. Condición: Brand New. 2013 edition. 127 pages. 9.25x0.31x6.10 inches. In Stock.

  • Idioma: Inglés

    Editorial: Springer, 2012

    1461460395 / 9781461460398

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes' theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes' theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes' theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes' model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes' theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences. …

  • Idioma: Inglés

    Editorial: Springer New York, 2012

    1461460395 / 9781461460398

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    Librería: Buchpark, Trebbin, AlemaniaBuchpark

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    Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes¿ theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes¿ theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes¿ theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes¿ model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study.  Very little has been published in the area of discrete Bayes¿ theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences. …

  • Idioma: Inglés

    Editorial: Springer, 2012

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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  • Idioma: Inglés

    Editorial: Springer 2012-12, 2012

    1461460395 / 9781461460398

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    Librería: Chiron Media, Wallingford, Reino UnidoChiron Media

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    PF. Condición: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Idioma: Inglés

    Editorial: Springer New York Dez 2012, 2012

    1461460395 / 9781461460398

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes' theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes' theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes' theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes' model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes' theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences. 128 pp. Englisch.…

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    Editorial: Springer New York, 2012

    1461460395 / 9781461460398

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    Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Important information for statisticians and researchers in the fields of engineering, computing, life sciences, and social sciencesStrategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer o.…

  • Idioma: Inglés

    Editorial: Springer, Springer Dez 2012, 2012

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes¿ theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes¿ theorem,walkingthem through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes¿ theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes¿ model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes¿ theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.…