TY - BOOK AU - Wilson,J.Holton AU - Keating,Barry P. AU - Beal-Hodges,Mary TI - Regression analysis: understanding and building business and economic models using Excel T2 - Quantitative approaches to decision making collection, SN - 9781606494356 AV - QA278.2 PY - 2012///.] CY - [New York, N.Y.] (222 East 46th Street, New York, NY 10017) PB - Business Expert Press KW - Microsoft Excel (Computer file) KW - Regression analysis KW - Econometric models KW - ordinary least squares (OLS) KW - time-series data KW - cross-sectional data KW - dependent variables KW - independent variables KW - point estimates KW - interval estimates KW - hypothesis testing KW - statistical significance KW - confidence level KW - significance level KW - p-value KW - R-squared KW - coefficient of determination KW - multicollinearity KW - correlation KW - serial correlation KW - seasonality KW - qualitative events KW - dummy variables KW - non-linear regression models KW - market share regression model KW - Abercrombie & Fitch Co KW - [genre] N1 - 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; 2; b; Also available in printing N2 - 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 UR - https://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000138.html ER -