Multiple Regression
eBook - ePub

Multiple Regression

A Practical Introduction

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Multiple Regression

A Practical Introduction

About this book

Multiple Regression: A Practical Introduction is a text for an advanced undergraduate or beginning graduate course in statistics for social science and related fields. Also, students preparing for more advanced courses can self-study the text to refresh and solidify their statistical background. Drawing on decades of teaching this material, the authors present the ideas in an approachable and nontechnical manner, with no expectation that readers have more than a standard introductory statistics course as background. Multiple regression asks how a dependent variable is related to, or predicted by, a set of independent variables. The book includes many interesting example analyses and interpretations, along with exercises. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered.

A website for the book includes SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book. Solutions to two of the end-of-chapter exercise types are also available for students to practice. The instructor side of the site contains editable PowerPoint slides, other solutions, and a test bank.

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Yes, you can access Multiple Regression by Aki Roberts,John M. Roberts, Jr. in PDF and/or ePUB format, as well as other popular books in Social Sciences & Criminology. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Publisher Note
  4. Title Page
  5. Copyright Page
  6. • Brief Contents •
  7. • Detailed Contents •
  8. • Preface •
  9. • Digital Resources •
  10. • About the Authors •
  11. • Acknowledgments •
  12. 1 Introduction
  13. 2 Fundamentals of Multiple Regression
  14. 3 Categorical Independent Variables in Multiple Regression Dummy Variables
  15. 4 Multiple Regression With Interaction
  16. 5 Logged Variables in Multiple Regression
  17. 6 Nonlinear Relationships in Multiple Regression
  18. 7 Categorical Dependent Variables Logistic Regression
  19. 8 Count Dependent Variables Poisson Regression
  20. 9 A Brief Tour of Some Related Methods
  21. APPENDIX A • F Distribution
  22. APPENDIX B • Chi-Square Distribution
  23. Glossary
  24. References
  25. Index