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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with 'too many variables to analyze and not enough observations,' and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve 'safe data mining'. There are many books that are excellent sources of knowledge about individual stastical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield '.students typically know the technical details of regressin for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and in statistical teaching between techniques and problem solving strategies.' Whether analyzing risk factors, adjusting for biases in observational studies, or developing predictive models, there are common problems that few regression texts address. For example, there are missing data in the majority of datasets one is likely to encounter (other than those used in textbooks!) but most regression texts do not include methods for dealing with such data effectively, and texts on missing data do not cover regression modeling.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Regression Modeling Strategies | With Applications to Linear Models, Logistic Regression, and Survival Analysis | Frank E. Harrell | Taschenbuch | xxiv | Englisch | 2010 | Springer | EAN 9781441929181 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer New York, Springer New York Dez 2010, 2010
ISBN 10: 1441929185 ISBN 13: 9781441929181
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with 'too many variables to analyze and not enough observations,' and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve 'safe data mining'.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 596 pp. Englisch.
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Añadir al carritoPaperback. Condición: Like New. Like New. book.
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Publicado por Springer New York Dez 2010, 2010
ISBN 10: 1441929185 ISBN 13: 9781441929181
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with 'too many variables to analyze and not enough observations,' and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve 'safe data mining'. There are many books that are excellent sources of knowledge about individual stastical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield '.students typically know the technical details of regressin for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and in statistical teaching between techniques and problem solving strategies.' Whether analyzing risk factors, adjusting for biases in observational studies, or developing predictive models, there are common problems that few regression texts address. For example, there are missing data in the majority of datasets one is likely to encounter (other than those used in textbooks!) but most regression texts do not include methods for dealing with such data effectively, and texts on missing data do not cover regression modeling. 596 pp. Englisch.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Written by a well-known biostatistical researcher and expert on S-PlusProvides full-scale case studies of non-trivial datasetsCase studies use S-PLUSMany texts are excellent sources of knowledge about individual statistical tools, b.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoCondición: new. Questo è un articolo print on demand.