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
- Cover
- Halftitle
- Titlepage
- Copyright
- Dedication
- Abstract
- Contents
- Foreword
- Acknowledgements
- Introduction
- Chapter 1 The Concept of Regression
- Chapter 2 The Method of Least Squares
- Chapter 3 Simple Linear Regression in Excel
- Chapter 4 Multiple Regression
- Chapter 5 Goodness of Fit
- Chapter 6 Regression Coefficients
- Chapter 7 Causality: Correlation is not Causality
- Chapter 8 Qualitative Variables in Regression
- Chapter 9 Pitfalls of Regression Analysis
- Appendix
- Glossary
- Notes
- References
- Index
- Lastpage
- Backcover
Product information
- Title: Regression for Economics
- Author(s):
- Release date: September 2012
- Publisher(s): Business Expert Press
- ISBN: 9781606494066
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