This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math. Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions.
This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math. Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions.
Jeremy Arkes is a retired economics professor from the Graduate School of Business and Public Policy, Naval Postgraduate School, U.S.A. He is currently writing books on economics, nature, and basketball.
Inhaltsangabe
1. Introduction 2. Regression analysis basics 3. Essential tools for regression analysis 4. What does "holding other factors constant" mean? 5. Standard errors, hypothesis tests, p-values, and aliens 6. What could go wrong when estimating causal effects? 7. Strategies for other regression objectives 8. Methods to address biases 9. Other methods besides Ordinary Least Squares 10. Time-series models 11. Some really interesting research 12. How to conduct a research project 13. The ethics of regression analysis 14. Summarizing thoughts Appendix of background statistical tools
1. Introduction 2. Regression analysis basics 3. Essential tools for regression analysis 4. What does "holding other factors constant" mean? 5. Standard errors, hypothesis tests, p-values, and aliens 6. What could go wrong when estimating causal effects? 7. Strategies for other regression objectives 8. Methods to address biases 9. Other methods besides Ordinary Least Squares 10. Time-series models 11. Some really interesting research 12. How to conduct a research project 13. The ethics of regression analysis 14. Summarizing thoughts Appendix of background statistical tools
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