Regression for economics /
Naghshpour, Shahdad,
Regression for economics / Shahdad Naghshpour. - 1st ed. - 1 electronic text (xix, 140 pages) : digital file. - Economics and finance collection, 2163-7628 . - 2012 digital library. Economics and finance collection. .
Part of: 2012 digital library.
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.
Access restricted to authorized users and institutions.
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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781606494066
10.4128/9781606494066 doi
Economics--Statistical methods.
Regression analysis.
regression analysis causality inference
[genre]
HB137
Regression for economics / Shahdad Naghshpour. - 1st ed. - 1 electronic text (xix, 140 pages) : digital file. - Economics and finance collection, 2163-7628 . - 2012 digital library. Economics and finance collection. .
Part of: 2012 digital library.
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.
Access restricted to authorized users and institutions.
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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781606494066
10.4128/9781606494066 doi
Economics--Statistical methods.
Regression analysis.
regression analysis causality inference
[genre]
HB137