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Regression analysis : understanding and building business and economic models using Excel / J. Holton Wilson, Barry P. Keating, and Mary Beal-Hodges.

By: Contributor(s): Material type: TextTextSeries: 2012 digital library | Quantitative approaches to decision making collectionPublisher: [New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Business Expert Press, [(c)2012.]Edition: 1st edDescription: 1 electronic text (179 pages) : digital fileContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781606494356
Subject(s): Genre/Form: Additional physical formats: Print version:: No titleLOC classification:
  • QA278.2
Online resources: Available additional physical forms:
Contents:
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 and Fitch Company regression case study -- 11. The formal ordinary least squares (OLS) regression model -- Appendix. Some statistical background -- Index.
Abstract: 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.
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Part of: 2012 digital library.

Includes index.

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 and Fitch Company regression case study -- 11. The formal ordinary least squares (OLS) regression model -- Appendix. Some statistical background -- Index.

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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.

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