Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
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Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
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Language: English
Published by Taylor and Francis Ltd, GB, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Paperback. Condition: New. 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.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
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Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
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Add to basketpaperback. Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
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Condition: New.
Paperback. Condition: Brand New. 424 pages. 9.18x6.12x1.00 inches. In Stock.
Language: English
Published by Taylor and Francis Ltd, GB, 2022
ISBN 10: 0367749122 ISBN 13: 9780367749125
Seller: Rarewaves.com UK, London, United Kingdom
Paperback. Condition: New. 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.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
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Language: English
Published by Taylor & Francis Group, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 608.
Language: English
Published by Chapman and Hall/CRC 2021-03-29, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: Chiron Media, Wallingford, United Kingdom
Hardcover. Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
£ 143.99
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Add to basketCondition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
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£ 164.74
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Add to basketCondition: New. In.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
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Hardcover. Condition: New. New. book.
Hardcover. Condition: Brand New. 423 pages. 9.50x6.25x1.25 inches. In Stock.
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: 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.
Language: English
Published by Taylor & Francis Group, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 608 Illus.
Language: English
Published by Taylor & Francis Group, 2021
ISBN 10: 158488939X ISBN 13: 9781584889397
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 608.
Seller: moluna, Greven, Germany
Gebunden. Condition: 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.