Wolfgang wiedermann (152 resultados)

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Paperback or Softback. Condición: New. Direction Dependence Analysis: Foundations and Statistical Methods. Book.

Hardcover. Condición: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.…

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paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Paperback. Condición: New. While regression analysis is widely understood, it falls short in determining the causal direction of relationships in observational data. In this groundbreaking volume, Wiedermann and von Eye introduce Direction Dependence Analysis (DDA), a novel method that leverages variable information often overlooked by traditional techniques, such as higher-order moments like skewness and kurtosis. DDA reveals the asymmetry properties of regression and correlation, enabling researchers to evaluate competing causal hypotheses, assess the roles of variables in causal flows, and develop statistical methods for testing causal direction. This book provides a comprehensive formal description of DDA, illustrated with both artificial and real-world data examples. Additionally, readers will find free software implementations of DDA, making this an essential resource for researchers seeking to enhance their understanding of causal relationships in data analysis.…

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Paperback. Condición: Brand New. 125 pages. 8.54x5.47x0.43 inches. In Stock.

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Condición: New. In English.

Paperback. Condición: Brand New. 406 pages. 6.00x0.80x9.00 inches. In Stock.

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Paperback. Condición: Brand New. 406 pages. 6.00x0.80x9.00 inches. In Stock.

hardcover. Condición: Fine.

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Paperback. Condición: new. Paperback. Dieser Band stellt umfassend die Methoden der Konfigurationsfrequenzanalyse (KFA) vor, eines von G.A. Lienert erstmals eingebrachten Verfahrens zur Testung von Hypothesen in Bezug auf Haeufigkeiten in individuellen Zellen oder Gruppen einer Kreuzklassifikation. Die Autoren, die die Methode weiterentwickelt haben, bieten eine umfassende Darstellung der Grundlagen, Modelle und konkreten Anwendungsfaelle in der psychologischen und sozialwissenschaftlichen, personen-orientierten Forschung. Dabei werden die Anfaenge der KFA und ihr Bezug zur Chi-Quadrat Analyse ebenso beschrieben wie die Entwicklungen, die auf log-linearen Modellen basieren. Fuer jedes Modell und fuer jede Fragestellung, die mit der KFA untersucht werden koennen, werden empirische Datenbeispiele praesentiert. Neue Ergebnisse werden durch Monte-Carlo Simulationen untermauert sowie neue Modelle entwickelt und vorgestellt.Das Buch richtet sich zum einen an Leser*innen, die ueber grundlegendes Hintergrundwissen in der angewandten Statistik aus einfuehrenden Kursen und Kursen ueber log-lineare Modelle verfuegen. Aber auch Leserinnen und Leser ohne diese Kenntnisse koennen von diesem Buch profitieren, weil alle noetigen technischen Elemente eigens eingefuehrt und erklaert werden. Computerprogramme werden vorgestellt und in Beispielen angewendet. Insgesamt stellt sich die KFA als statistische Methode dar, mit der fuer kategoriale Daten wichtige und interessante Fragen bearbeitet werden koennen, die im Kontext der Anwendung von Routinemethoden der Statistik nicht zugaenglich sind. Insgesamt stellt sich die KFA als statistische Methode dar, mit der fuer kategoriale Daten wichtige und interessante Fragen bearbeitet werden koennen, die im Kontext der Anwendung von Routinemethoden der Statistik nicht zugaenglich sind. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Taschenbuch. Condición: Neu. Neuware - General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained from weighted independent variables plus an additive error term that reflects imperfections of the model and measurement error. It also covers multivariate regression, analysis of variance, analysis under consideration of covariates, variable selection methods, symmetric regression, and the recently developed methods of recursive partitioning and direction dependence analysis. Each method is formally derived and embedded in the GLM, and characteristics of these methods are highlighted. Real-world data examples illustrate the application of each of these methods, and it is shown how results can be interpreted.…

Condición: New. &Uumlber den AutorAlexander von Eye is Professor Emeritus of Psychology at Michigan State University, USA. He received his Ph.D. in Psychology from the University of Trier, Germany, in 1976. He is known for his work on statistical model.

hardcover. Condición: Very Good.

Paperback. Condición: new. Paperback. While regression analysis is widely understood, it falls short in determining the causal direction of relationships in observational data. In this groundbreaking volume, Wiedermann and von Eye introduce Direction Dependence Analysis (DDA), a novel method that leverages variable information often overlooked by traditional techniques, such as higher-order moments like skewness and kurtosis. DDA reveals the asymmetry properties of regression and correlation, enabling researchers to evaluate competing causal hypotheses, assess the roles of variables in causal flows, and develop statistical methods for testing causal direction. This book provides a comprehensive formal description of DDA, illustrated with both artificial and real-world data examples. Additionally, readers will find free software implementations of DDA, making this an essential resource for researchers seeking to enhance their understanding of causal relationships in data analysis. Discover the groundbreaking Direction Dependence Analysis (DDA), a powerful statistical method that enhances traditional regression and structural modeling by evaluating causal direction between variables. This book offers formal DDA methodologies, real-world applications, and introduces user-friendly DDA software for effective data analysis. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - While regression analysis is widely understood, it falls short in determining the causal direction of relationships in observational data. In this groundbreaking volume, Wiedermann and von Eye introduce Direction Dependence Analysis (DDA), a novel method that leverages variable information often overlooked by traditional techniques, such as higher-order moments like skewness and kurtosis. DDA reveals the asymmetry properties of regression and correlation, enabling researchers to evaluate competing causal hypotheses, assess the roles of variables in causal flows, and develop statistical methods for testing causal direction. This book provides a comprehensive formal description of DDA, illustrated with both artificial and real-world data examples. Additionally, readers will find free software implementations of DDA, making this an essential resource for researchers seeking to enhance their understanding of causal relationships in data analysis.…

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Condición: New.