An R Companion to Applied Regression
eBook - ePub

An R Companion to Applied Regression

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

An R Companion to Applied Regression

About this book

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials.

The Third Edition has been reorganized and includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this edition, introducing additional capabilities and making the software more consistent and easier to use. They also advocate an everyday data-analysis workflow that encourages reproducible research. To this end, they provide coverage of RStudio, an interactive development environment for R that allows readers to organize and document their work in a simple and intuitive fashion, and then easily share their results with others. Also included is coverage of R Markdown, showing how to create documents that mix R commands with explanatory text. 

"An R Companion to Applied Regression continues to provide the most comprehensive and user-friendly guide to estimating, interpreting, and presenting results from regression models in R."

–Christopher Hare, University of California, Davis

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Yes, you can access An R Companion to Applied Regression by John Fox,Sanford Weisberg in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Acknowledgements
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Publisher Note
  8. Preface
  9. About the Authors
  10. 1 Getting Started With R and RStudio
  11. 2 Reading and Manipulating Data
  12. 3 Exploring and Transforming Data
  13. 4 Fitting Linear Models
  14. 5 Coefficient Standard Errors, Confidence Intervals, and Hypothesis Tests
  15. 6 Fitting Generalized Linear Models
  16. 7 Fitting Mixed-Effects Models
  17. 8 Regression Diagnostics for Linear, Generalized Linear, and Mixed-Effects Models
  18. 9 Drawing Graphs
  19. 10 An Introduction to R Programming
  20. References
  21. Subject Index
  22. Data Set Index
  23. Data Set Index
  24. Data Set Index