Rodrigues recchia daniela (8 risultati)

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  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

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    Da: Books Puddle, Woodside, NY, U.S.A.Books Puddle

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    Condizione: Nuovo

    EUR 75,43

    EUR 3,55 spedizione 
    Spedito in U.S.A.

    Quantità: 4 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

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    Da: preigu, Osnabrück, Germaniapreigu

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    Condizione: Nuovo

    EUR 40,20

    EUR 70,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 5 disponibili

    Taschenbuch. Condizione: Neu. A Comparison of Two Methods in Credit Scoring | with Application on Metro Data | Daniela Rodrigues Recchia | Taschenbuch | 124 S. | Englisch | 2013 | AV Akademikerverlag | EAN 9783639479539 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. …

  • Lingua: Inglese

    Editore: AV Akademikerverlag Sep 2013, 2013

    363947953X / 9783639479539

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    • Print on Demand

    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Condizione: Nuovo

    EUR 44,90

    EUR 23,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The credit scoring methodology is increasingly used in companies and business field. This method once in the 1950 s introduced has developed and cover new branches today, such as mailing and fraud. This methodology is one of the most important to manage risks and estimate the probability of default of a client by borrowing money. There are several statistical methods to select the relevant characteristics for the scoring model such as linear regression models and classification tree and the goal in this study is to compare the two most used statistical methods on credit scoring: logistic regression - with categorized and raw data - and discriminant analysis, as also their pros and cons. The analysis was made using a dataset from METRO Cash&Carry enabling the application of the methods on real data. The logistic regression with a Scorecard example and the discriminant analysis have a similar performance on estimating the probability of default from a client, despite the methodologies being different the approaches are similar and the results shown a small difference between them. 124 pp. Englisch. …

  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

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    • Print on Demand

    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: Nuovo

    EUR 74,76

    EUR 7,65 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

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    • Print on Demand

    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    Condizione: Nuovo

    EUR 74,50

    EUR 9,95 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. PRINT ON DEMAND.

  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

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    • Print on Demand

    Da: moluna, Greven, Germaniamoluna

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    Condizione: Nuovo

    EUR 36,33

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rodrigues Recchia DanielaDaniela Rodrigues Recchia, M.Sc. in Statistics: Master of Science in Statistics at the Technische Universitaet Dortmund, Germany. Bachelor in Statistics at the State University of Campinas, Brazil. Professiona.…

  • Lingua: Inglese

    Editore: AV Akademikerverlag Sep 2013, 2013

    363947953X / 9783639479539

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 44,90

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The credit scoring methodology is increasingly used in companies and business field. This method once in the 1950's introduced has developed and cover new branches today, such as mailing and fraud. This methodology is one of the most important to manage risks and estimate the probability of default of a client by borrowing money. There are several statistical methods to select the relevant characteristics for the scoring model such as linear regression models and classification tree and the goal in this study is to compare the two most used statistical methods on credit scoring: logistic regression - with categorized and raw data - and discriminant analysis, as also their pros and cons. The analysis was made using a dataset from METRO Cash&Carry enabling the application of the methods on real data. The logistic regression with a Scorecard example and the discriminant analysis have a similar performance on estimating the probability of default from a client, despite the methodologies being different the approaches are similar and the results shown a small difference between them.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch.…

  • Lingua: Inglese

    Editore: AV Akademikerverlag, 2013

    363947953X / 9783639479539

    • Brossura
    • Print on Demand

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 44,90

    EUR 61,02 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The credit scoring methodology is increasingly used in companies and business field. This method once in the 1950 s introduced has developed and cover new branches today, such as mailing and fraud. This methodology is one of the most important to manage risks and estimate the probability of default of a client by borrowing money. There are several statistical methods to select the relevant characteristics for the scoring model such as linear regression models and classification tree and the goal in this study is to compare the two most used statistical methods on credit scoring: logistic regression - with categorized and raw data - and discriminant analysis, as also their pros and cons. The analysis was made using a dataset from METRO Cash&Carry enabling the application of the methods on real data. The logistic regression with a Scorecard example and the discriminant analysis have a similar performance on estimating the probability of default from a client, despite the methodologies being different the approaches are similar and the results shown a small difference between them.…