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Book Description

Regression analysis is the most commonly used statistical method in the world. 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 and will help demystify regression analysis using examples from economics and with real data to show the applications of the method. The concepts related to regression analysis are explained in a way that is comprehensible to those whose mathematical skills are not matching that of the expert level, and uses Microsoft Excel to obtain regression results. What hinders peoples’ comprehension of regression analysis is the difficulty many have in understanding mathematical symbols and derivations. By removing this obstacle, this book enables the logical reader to learn regression without possessing superior mathematical skills.

Table of Contents

  1. Cover
  2. Halftitle
  3. Titlepage
  4. Copyright
  5. Dedication
  6. Abstract
  7. Contents
  8. Foreword
  9. Acknowledgements
  10. Introduction
  11. Chapter 1 The Concept of Regression
  12. Chapter 2 The Method of Least Squares
  13. Chapter 3 Simple Linear Regression in Excel
  14. Chapter 4 Multiple Regression
  15. Chapter 5 Goodness of Fit
  16. Chapter 6 Regression Coefficients
  17. Chapter 7 Causality: Correlation is not Causality
  18. Chapter 8 Qualitative Variables in Regression
  19. Chapter 9 Pitfalls of Regression Analysis
  20. Appendix
  21. Glossary
  22. Notes
  23. References
  24. Index
  25. Lastpage
  26. Backcover