Regression Analysis: a practical introduction/ Jeremy Arkes

Includes glossary, index

1. Introduction -- 2. Regression analysis basics -- 3. Essential tool for regression analysis -- 4. What does 'holding other factors constant' means? -- 5. Standard errors hypothesis tests p-values and aliens -- 6. What could go wrong when estimating casual 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. Summarizing thoughts -- Appendix of background statistical tools

This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand what regressions do, what their limitations are, and what they can tell us. This will be the most engaging book on regression analysis (or Econometrics).
the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research.