Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Idioma: Inglés
Publicado por Cambridge University Press, GB, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
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Añadir al carritoHardcover. Condición: Brand New. 75 pages. 6.00x0.31x9.00 inches. In Stock.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: Rarewaves.com UK, London, Reino Unido
EUR 72,14
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 81,69
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Añadir al carritoHardcover. Condición: 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.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 75 pages. 6.00x0.31x9.00 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: CitiRetail, Stevenage, Reino Unido
EUR 78,69
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Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 102,09
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Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2024
ISBN 10: 1009494694 ISBN 13: 9781009494694
Librería: preigu, Osnabrück, Alemania
EUR 85,20
Cantidad disponible: 5 disponibles
Añadir al carritoBuch. Condición: 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.