Regression for economics / Shahdad Naghshpour.

Includes bibliographical references (page [135]) and index.

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.