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Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Published by Oxford University Press, Oxford, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Paperback. Condition: new. Paperback. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three part-text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks.Part I, Talking Probabilityexplains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learningunknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners,while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program in data science without knowing enough statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Paperback. Condition: Brand New. 176 pages. 9.25x6.18x0.35 inches. In Stock.
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Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Hardcover. Condition: Brand New. 176 pages. 9.37x6.30x0.55 inches. In Stock.
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Published by Oxford University Press, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
Seller: moluna, Greven, Germany
Condition: New. Über den AutorMu Zhu is Professor in the Department of Statistics & Actuarial Science at the University of Waterloo, and Fellow of the American Statistical Association. He received his AB magna cum laude in applied mathematics from .
Language: English
Published by Oxford University Press, Oxford, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three-part text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks.Part I, Talking Probabilityexplains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learningunknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners,while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text. Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program in data science without knowing enough statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
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Published by Oxford University Press Jul 2023, 2023
ISBN 10: 0192867741 ISBN 13: 9780192867742
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Taschenbuch. Condition: Neu. Neuware - Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three part-text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks.Part I, Talking Probability explains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learning unknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text.
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 176 pages. 9.37x6.30x0.55 inches. In Stock.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
Seller: moluna, Greven, Germany
Condition: New. Über den AutorMu Zhu is Professor in the Department of Statistics & Actuarial Science at the University of Waterloo, and Fellow of the American Statistical Association. He received his AB magna cum laude in applied mathematics from .
Language: English
Published by Oxford University Press Jul 2023, 2023
ISBN 10: 0192867733 ISBN 13: 9780192867735
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware - Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three-part text starts from the basics of probability and random variables and guides readers towards relatively advanced topics in both frequentist and Bayesian approaches in a matter of weeks. Part I, Talking Probability explains that the statistical approach to analysing data starts with a probability model to describe the data generating process. Part II, Doing Statistics explains that much of statistical inference is about learning unknown quantities in the model (e.g. its parameters) from the data it is presumed to have generated. Part III, Facing Uncertainty explains the importance of explicitly describing how much uncertainty we have about the model parameters, especially those with intrinsic scientific meaning, and of taking that into account when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more serious than a typical undergraduate text, but still lighter and more accessible than an average graduate text.