Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloHardback. Condizione: New. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout.
Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
Editore: Cambridge University Press, 2024
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Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
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ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
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ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloHardback. Condizione: New. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout.
Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. The readers will understand Bayesian theory and practice using social science data.
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Editore: Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Hardcover. Condizione: new. Hardcover. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. The readers will understand Bayesian theory and practice using social science data. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Da: Biblios, Frankfurt am main, HESSE, Germania
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Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. The readers will understand Bayesian theory and practice using social science data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. The readers will understand Bayesian theory and practice using social science data. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Aggiungi al carrelloBuch. Condizione: Neu. Bayesian Social Science Statistics | Jeff Gill (u. a.) | Buch | Englisch | 2024 | Cambridge University Press | EAN 9781009494694 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.