Using R and RStudio for Data Management, Statistical Analysis, and Graphics, 2nd Edition

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, 2nd Edition

by Nicholas J. Horton, Ken Kleinman
Released March 2015
Publisher(s): Chapman and Hall/CRC
ISBN: 9781482237375

Explore a preview version of Using R and RStudio for Data Management, Statistical Analysis, and Graphics, 2nd Edition right now.

O’Reilly members get unlimited access to live online training experiences, plus books, videos, and digital content from 200+ publishers.

Start your free trial

Book description

Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition

The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
New chapter on simulation that includes examples of data generated from complex models and distributions
A detailed discussion of the philosophy and use of the knitr and markdown packages for R
New packages that extend the functionality of R and facilitate sophisticated analyses
Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots

Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.

Table of contents

  1. Front Cover
  2. Contents (1/3)
  3. Contents (2/3)
  4. Contents (3/3)
  5. List of Tables
  6. List of Figures
  7. Preface to the second edition
  8. Preface to the rst edition
  9. Chapter 1: Data input and output (1/2)
  10. Chapter 1: Data input and output (2/2)
  11. Chapter 2: Data management (1/5)
  12. Chapter 2: Data management (2/5)
  13. Chapter 2: Data management (3/5)
  14. Chapter 2: Data management (4/5)
  15. Chapter 2: Data management (5/5)
  16. Chapter 3: Statistical and mathematical functions (1/3)
  17. Chapter 3: Statistical and mathematical functions (2/3)
  18. Chapter 3: Statistical and mathematical functions (3/3)
  19. Chapter 4: Programming and operating system interface (1/2)
  20. Chapter 4: Programming and operating system interface (2/2)
  21. Chapter 5: Common statistical procedures (1/4)
  22. Chapter 5: Common statistical procedures (2/4)
  23. Chapter 5: Common statistical procedures (3/4)
  24. Chapter 5: Common statistical procedures (4/4)
  25. Chapter 6: Linear regression and ANOVA (1/5)
  26. Chapter 6: Linear regression and ANOVA (2/5)
  27. Chapter 6: Linear regression and ANOVA (3/5)
  28. Chapter 6: Linear regression and ANOVA (4/5)
  29. Chapter 6: Linear regression and ANOVA (5/5)
  30. Chapter 7: Regression generalizations and modeling (1/7)
  31. Chapter 7: Regression generalizations and modeling (2/7)
  32. Chapter 7: Regression generalizations and modeling (3/7)
  33. Chapter 7: Regression generalizations and modeling (4/7)
  34. Chapter 7: Regression generalizations and modeling (5/7)
  35. Chapter 7: Regression generalizations and modeling (6/7)
  36. Chapter 7: Regression generalizations and modeling (7/7)
  37. Chapter 8: A graphical compendium (1/5)
  38. Chapter 8: A graphical compendium (2/5)
  39. Chapter 8: A graphical compendium (3/5)
  40. Chapter 8: A graphical compendium (4/5)
  41. Chapter 8: A graphical compendium (5/5)
  42. Chapter 9: Graphical options and con guration (1/2)
  43. Chapter 9: Graphical options and con guration (2/2)
  44. Chapter 10: Simulation (1/3)
  45. Chapter 10: Simulation (2/3)
  46. Chapter 10: Simulation (3/3)
  47. Chapter 11: Special topics (1/4)
  48. Chapter 11: Special topics (2/4)
  49. Chapter 11: Special topics (3/4)
  50. Chapter 11: Special topics (4/4)
  51. Chapter 12: Case studies (1/5)
  52. Chapter 12: Case studies (2/5)
  53. Chapter 12: Case studies (3/5)
  54. Chapter 12: Case studies (4/5)
  55. Chapter 12: Case studies (5/5)
  56. Appendix A: Introduction to R and RStudio (1/6)
  57. Appendix A: Introduction to R and RStudio (2/6)
  58. Appendix A: Introduction to R and RStudio (3/6)
  59. Appendix A: Introduction to R and RStudio (4/6)
  60. Appendix A: Introduction to R and RStudio (5/6)
  61. Appendix A: Introduction to R and RStudio (6/6)
  62. Appendix B: The HELP study dataset (1/2)
  63. Appendix B: The HELP study dataset (2/2)
  64. Appendix C: References (1/3)
  65. Appendix C: References (2/3)
  66. Appendix C: References (3/3)
  67. Back Cover

Product information

  • Title: Using R and RStudio for Data Management, Statistical Analysis, and Graphics, 2nd Edition
  • Author(s): Nicholas J. Horton, Ken Kleinman
  • Release date: March 2015
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781482237375