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Applied regression analysis for busi...

Esquerdo, Pedro J. Rodriguez.

Applied regression analysis for businesstools, traps and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applied regression analysis for businessby Jacek Welc, Pedro J. Rodriguez Esquerdo.
其他題名:	tools, traps and applications /
作者:	Welc, Jacek.
其他作者:	Esquerdo, Pedro J. Rodriguez.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xi, 286 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Regression analysisMathematical models.
電子資源:	http://dx.doi.org/10.1007/978-3-319-71156-0
ISBN:	9783319711560$q(electronic bk.)

Applied regression analysis for businesstools, traps and applications /
Welc, Jacek.

Applied regression analysis for businesstools, traps and applications /[electronic resource] :by Jacek Welc, Pedro J. Rodriguez Esquerdo. - Cham :Springer International Publishing :2018. - xi, 286 p. :ill., digital ;24 cm.

Preface -- Basics of regression models -- Relevance of outlying and influential observations for regression analysis -- Basic procedure for multiple regression model building -- Verification of multiple regression model -- Common adjustments to multiple regressions -- Common pitfalls in regression analysis -- Regression analysis of discrete dependent variables -- Real-life case-study: The quarterly sales revenues of Nokia Corporation -- Real-life case-study: Identifying overvalued and undervalued airlines -- Appendix: Statistical Tables.

This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.

ISBN: 9783319711560$q(electronic bk.)

Standard No.: 10.1007/978-3-319-71156-0doiSubjects--Topical Terms:

405172
Regression analysis
--Mathematical models.

LC Class. No.: HA31.3 / .W453 2018

Dewey Class. No.: 330.0151

Applied regression analysis for businesstools, traps and applications /
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505 0 $a Preface -- Basics of regression models -- Relevance of outlying and influential observations for regression analysis -- Basic procedure for multiple regression model building -- Verification of multiple regression model -- Common adjustments to multiple regressions -- Common pitfalls in regression analysis -- Regression analysis of discrete dependent variables -- Real-life case-study: The quarterly sales revenues of Nokia Corporation -- Real-life case-study: Identifying overvalued and undervalued airlines -- Appendix: Statistical Tables.
520 $a This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.
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