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Book Description

Summary

R in Action is the first book to present both the R system and the use cases that make it such a compelling package for business developers. The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.

About the Technology

R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.

About the Book

R in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually.

What's Inside

  • Practical data analysis, step by step

  • Interfacing R with other software

  • Using R to visualize data

  • Over 130 graphs

  • Eight reference appendixes

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Table of Contents


Part I Getting started

  1. Introduction to R

  2. Creating a dataset

  3. Getting started with graphs

  4. Basic data management

  5. Advanced data management

    Part II Basic methods

  6. Basic graphs

  7. Basic statistics

    Part III Intermediate methods

  8. Regression

  9. Analysis of variance

  10. Power analysis

  11. Intermediate graphs

  12. Re-sampling statistics and bootstrapping

    Part IV Advanced methods

  13. Generalized linear models

  14. Principal components and factor analysis

  15. Advanced methods for missing data

  16. Advanced graphics

Table of Contents

  1. Copyright
  2. Brief Table of Contents
  3. Table of Contents
  4. Preface
  5. Acknowledgments
  6. About this Book
  7. About the Cover Illustration
  8. Part 1. Getting started
  9. Chapter 1. Introduction to R
  10. Chapter 2. Creating a dataset
  11. Chapter 3. Getting started with graphs
  12. Chapter 4. Basic data management
  13. Chapter 5. Advanced data management
  14. Part 2. Basic methods
  15. Chapter 6. Basic graphs
  16. Chapter 7. Basic statistics
  17. Part 3. Intermediate methods
  18. Chapter 8. Regression
  19. Chapter 9. Analysis of variance
  20. Chapter 10. Power analysis
  21. Chapter 11. Intermediate graphs
  22. Chapter 12. Resampling statistics and bootstrapping
  23. Part 4. Advanced methods
  24. Chapter 13. Generalized linear models
  25. Chapter 14. Principal components and factor analysis
  26. Chapter 15. Advanced methods for missing data
  27. Chapter 16. Advanced graphics
  28. Appendix. afterword: Into the rabbit hole
  29. Appendix A. Graphic user interfaces
  30. Appendix B. Customizing the startup environment
  31. Appendix C. Exporting data from R
  32. Appendix D. Creating publication-quality output
  33. Appendix E. Matrix Algebra in R
  34. Appendix F. Packages used in this book
  35. Appendix G. Working with large datasets
  36. Appendix H. Updating an R installation
  37. Appendix. References
  38. Index
  39. List of Figures
  40. List of Tables
  41. List of Listings