Multicollinearity in Regression Analysis: The Problem Revisited (Classic Reprint) - Couverture souple

D. E. Farrar

9781332270804: Multicollinearity in Regression Analysis: The Problem Revisited (Classic Reprint)

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ISBN 10 : 1332270808 ISBN 13 : 9781332270804

Editeur : Forgotten Books, 2018

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�diteur: Forgotten Books
Date d'�dition: 2018
Langue: anglais
ISBN 10: 1332270808
ISBN 13: 9781332270804
Reliure: Broch�
Nombre de pages: 58
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Multicollinearity in Regression Analysis: The Problem Revisited

D. E. Farrar, R. R. Glauber

Edit� par Forgotten Books, 2018

ISBN 10 : 1332270808 ISBN 13 : 9781332270804

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Vendeur : Forgotten Books, London, Royaume-Uni

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Paperback. Etat : New. Print on Demand. This book explores the phenomenon of multicollinearity, a statistical condition in which high intercorrelations exist within a set of explanatory variables in regression analysis. The author argues that multicollinearity is a significant problem that can undermine the reliability of parameter estimates and lead to erroneous conclusions. The book provides a comprehensive analysis of multicollinearity, tracing its historical development and examining its impact on econometric modeling. The author introduces a novel three-stage diagnostic approach to detect, locate, and analyze the pattern of interdependence within an independent variable set. These diagnostics can help researchers understand the nature and severity of multicollinearity, enabling them to take appropriate corrective actions to improve the accuracy of their models. Through detailed illustrations, the book demonstrates how multicollinearity can distort parameter estimates and hinder the identification of true relationships between variables. The author emphasizes the importance of distinguishing between the nature and effects of multicollinearity, and highlights the need for researchers to address the problem proactively rather than as an afterthought. By providing a systematic framework for understanding and addressing multicollinearity, this book offers valuable guidance to researchers and practitioners in econometrics and related fields. It contributes to a deeper understanding of the complexities of regression analysis, enabling users to produce more reliable and insightful results from their models. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. N� de r�f. du vendeur 9781332270804_0

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