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Regression analysis : understanding and building business and economic models using Excel /

Bibliographic Details
Main Authors: Wilson, J. Holton, 1942- (Author), Keating, Barry P. (Author), Beal-Hodges, Mary (Author)
Corporate Author: EBSCOhost
Format: eBook
Language:English
Published: New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2016.
Edition:Second edition.
Series:Quantitative approaches to decision making collection.
Subjects:
Regression analysis.
Econometric models.
Microsoft Excel (Computer file)
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
nonlinear regression models
market share regression model
Abercrombie & Fitch Co.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of 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 & Fitch and jewelry sales regression case studies
  • 11. The formal ordinary least squares (OLS) regression model
  • Appendix. Some statistical background
  • Index.