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Librería: Majestic Books, Hounslow, Reino Unido
EUR 66,89
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 70,24
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 75,21
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Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 67,89
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 70,05
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Publicado por Chapman and Hall/CRC 2022-09, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
EUR 69,24
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 72,64
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 76,72
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 79,20
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 94,56
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Añadir al carritoPaperback. Condición: Brand New. 424 pages. 9.18x6.12x1.00 inches. In Stock.
Librería: dsmbooks, Liverpool, Reino Unido
EUR 135,60
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Añadir al carritopaperback. Condición: New. New. SHIPS FROM MULTIPLE LOCATIONS. book.
Publicado por Chapman And Hall/CRC Sep 2022, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 60,80
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting.Features:-Complete introduction to mathematical probability, random variables, and distribution theory.-Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes.-Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference.-Detailed introduction to Bayesian statistics and associated topics.-Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC).This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields. 444 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 57,92
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Miltiadis Mavrakakis obtained his PhD in Statistics at LSE under the supervision of Jeremy Penzer. His first job was as a teaching fellow at LSE, taking over course ST202 and completing this book in the process. He splits his time between lecturing (at L.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 68,98
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Añadir al carritoPaperback. Condición: Brand New. 424 pages. 9.18x6.12x1.00 inches. In Stock. This item is printed on demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 69,82
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting.Features:-Complete introduction to mathematical probability, random variables, and distribution theory.-Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes.-Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference.-Detailed introduction to Bayesian statistics and associated topics.-Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC).This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.