Regression for economics [electronic resource] / Shahdad Naghshpour
- Naghshpour, Shahdad
- [New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2012.
- 1st ed.
- Physical Description:
- 1 electronic text (xix, 140 pages) : digital file
- Economics and finance collection, 2163-7628
- Restrictions on Access:
- Access restricted to authorized users and institutions.
- Foreword -- Acknowledgments -- Introduction -- 1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression in Excel -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary -- Notes -- References -- Index.
- The concept of regression was introduced by Sir Francis Galton, but R.A. Fisher provided the statistical theory and application for it for the first time. The 20th century witnessed the spread of regression analysis into every scientific branch. Regression analysis is the most commonly used statistical method in the world. It is used in economics and many other fields. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation of the regression analysis. All the examples are from economics, and in almost all the examples the real data is used to show the applications of the method.
- 9781606494066 (electronic bk.)
- Part of: 2012 digital library.
- Bibliography Note:
- Includes bibliographical references (pages 135-136) and index.
- Other Forms:
- Also available in print.
- Technical Details:
- Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
View MARC record | catkey: 22079948