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Aggiungi al carrelloCondizione: New. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psyc.
Da: Biblios, Frankfurt am main, HESSE, Germania
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Editore: Chapman and Hall/CRC 2022-03-21, 2022
ISBN 10: 0367408783 ISBN 13: 9780367408787
Lingua: Inglese
Da: Chiron Media, Wallingford, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action.Key Features:Description of regularization methods in a user friendly and easy to read mannerInclusion of regularization-based approaches for a variety of statistical analyses commonly used in the social sciences, including both univariate and multivariate modelsFully developed extended examples using multiple software packages, including R, SAS, and SPSSWebsite containing all datasets and software scripts used in the examplesInclusion of both frequentist and Bayesian regularization approachesApplication exercises for each chapter that instructors could use in class, and independent researchers could use to practice what they have learned from the book Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this book provides and overview of a variety of models alongside clear examples of hands-on application. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Da: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action.Key Features:Description of regularization methods in a user friendly and easy to read mannerInclusion of regularization-based approaches for a variety of statistical analyses commonly used in the social sciences, including both univariate and multivariate modelsFully developed extended examples using multiple software packages, including R, SAS, and SPSSWebsite containing all datasets and software scripts used in the examplesInclusion of both frequentist and Bayesian regularization approachesApplication exercises for each chapter that instructors could use in class, and independent researchers could use to practice what they have learned from the book Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this book provides and overview of a variety of models alongside clear examples of hands-on application. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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EUR 73,48
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action.Key Features:Description of regularization methods in a user friendly and easy to read mannerInclusion of regularization-based approaches for a variety of statistical analyses commonly used in the social sciences, including both univariate and multivariate modelsFully developed extended examples using multiple software packages, including R, SAS, and SPSSWebsite containing all datasets and software scripts used in the examplesInclusion of both frequentist and Bayesian regularization approachesApplication exercises for each chapter that instructors could use in class, and independent researchers could use to practice what they have learned from the book Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this book provides and overview of a variety of models alongside clear examples of hands-on application. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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EUR 156,06
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EUR 104,48
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.