1. Background issues for regression analysis -- 2. Introduction to regression analysis -- 3. The ordinary least squares (OLS) regression model -- 4. Evaluation of ordinary least squares (OLS) regression models -- 5. Point and interval estimates from a regression model -- 6. Multiple linear regressio...

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Bibliographic Details

Main Author:	Wilson, J. Holton 1942- (Author)
Format:	Electronic eBook
Language:	English
Published:	[New York, N.Y.] (222 East 46th Street, New York, NY 10017) Business Expert Press 2012
Edition:	1st ed
Series:	Quantitative approaches to decision making collection
Subjects:	Microsoft Excel (Computer file) Regression analysis Econometric models
Online Access:	FHN01 FWS01 FWS02 UBY01 Volltext
Summary:	1. Background issues for regression analysis -- 2. Introduction to regression analysis -- 3. The ordinary least squares (OLS) regression model -- 4. Evaluation of ordinary least squares (OLS) regression models -- 5. Point and interval estimates from a regression model -- 6. Multiple linear regression -- 7. A market share multiple regression model -- 8. Qualitative events and seasonality in multiple regression models -- 9. Nonlinear regression models -- 10. Abercrombie & Fitch Co. regression case study -- 11. The formal ordinary least squares (OLS) regression model -- Appendix. Some statistical background -- Index This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. It is especially useful for those engaged in working with numbers - preparing forecasts, budgeting, estimating the effects of business decisions, and any of the forms of analytics that have recently become so useful
Item Description:	Part of: 2012 digital library. - Includes index
Physical Description:	Online-Ressource (179 p.)
ISBN:	9781606494356