Isbn: 9783030713515 - data science for public policy (springer series in the data sciences) (2 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030713512 / 9783030713515

    Serie: Buch 7 von 11 - Springer Series in the Data Sciences

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Zustand: Neu

    EUR 102,63

    EUR 44,02 Versand 
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    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst's time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.…

  • Sprache: Englisch

    Verlag: Palgrave Macmillan, 2021

    3030713512 / 9783030713515

    Serie: Buch 7 von 11 - Springer Series in the Data Sciences

    • Hardcover

    Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

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    Zustand: Gebraucht - Sehr gut

    EUR 39,39

    EUR 105,00 Versand 
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    Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 380 | Sprache: Englisch | Produktart: Bücher | This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst¿s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.…