Regression analysis : understanding and building business and economic models using Excel /
Wilson, J. Holton, 1942-,
Regression analysis : understanding and building business and economic models using Excel / J. Holton Wilson, Barry P. Keating, and Mary Beal-Hodges. - 1st ed. - 1 electronic text (179 pages) : digital file. - Quantitative approaches to decision making collection, 2163-9582 . - 2012 digital library. Quantitative approaches to decision making collection. .
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.
Access restricted to authorized users and institutions.
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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781606494356
10.4128/9781606494356 doi
Microsoft Excel (Computer file)
Regression analysis.
Econometric models.
Regression analysis ordinary least squares (OLS) time-series data cross-sectional data, dependent variables independent variables point estimates interval estimates hypothesis testing statistical significance confidence level significance level p-value R-squared coefficient of determination multicollinearity correlation serial correlation seasonality qualitative events dummy variables non-linear regression models market share regression model Abercrombie & Fitch Co.
[genre]
QA278.2
Regression analysis : understanding and building business and economic models using Excel / J. Holton Wilson, Barry P. Keating, and Mary Beal-Hodges. - 1st ed. - 1 electronic text (179 pages) : digital file. - Quantitative approaches to decision making collection, 2163-9582 . - 2012 digital library. Quantitative approaches to decision making collection. .
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.
Access restricted to authorized users and institutions.
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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781606494356
10.4128/9781606494356 doi
Microsoft Excel (Computer file)
Regression analysis.
Econometric models.
Regression analysis ordinary least squares (OLS) time-series data cross-sectional data, dependent variables independent variables point estimates interval estimates hypothesis testing statistical significance confidence level significance level p-value R-squared coefficient of determination multicollinearity correlation serial correlation seasonality qualitative events dummy variables non-linear regression models market share regression model Abercrombie & Fitch Co.
[genre]
QA278.2