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Book Description

Summary

R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.

About the Technology

Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you’re likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide.

About the Book

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

What’s Inside

  • Complete R language tutorial

  • Using R to manage, analyze, and visualize data

  • Techniques for debugging programs and creating packages

  • OOP in R

  • Over 160 graphs

  • About the Author

    Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.

    Table of Contents

    1. Copyright
    2. Brief Table of Contents
    3. Table of Contents
    4. Praise for the First Edition
    5. Preface
    6. Acknowledgments
    7. About this Book
    8. About the Cover Illustration
    9. Part 1. Getting started
      1. Chapter 1. Introduction to R
      2. Chapter 2. Creating a dataset
      3. Chapter 3. Getting started with graphs
      4. Chapter 4. Basic data management
      5. Chapter 5. Advanced data management
    10. Part 2. Basic methods
      1. Chapter 6. Basic graphs
      2. Chapter 7. Basic statistics
    11. Part 3. Intermediate methods
      1. Chapter 8. Regression
      2. Chapter 9. Analysis of variance
      3. Chapter 10. Power analysis
      4. Chapter 11. Intermediate graphs
      5. Chapter 12. Resampling statistics and bootstrapping
    12. Part 4. Advanced methods
      1. Chapter 13. Generalized linear models
      2. Chapter 14. Principal components and factor analysis
      3. Chapter 15. Time series
      4. Chapter 16. Cluster analysis
      5. Chapter 17. Classification
      6. Chapter 18. Advanced methods for missing data
    13. Part 5. Expanding your skills
      1. Chapter 19. Advanced graphics with ggplot2
      2. Chapter 20. Advanced programming
      3. Chapter 21. Creating a package
      4. Chapter 22. Creating dynamic reports
    14. Afterword Into the rabbit hole
    15. Appendix A. Graphical user interfaces
    16. Appendix B. Customizing the startup environment
    17. Appendix C. Exporting data from R
    18. Appendix D. Matrix algebra in R
    19. Appendix E. Packages used in this book
    20. Appendix F. Working with large datasets
    21. Appendix G. Updating an R installation
    22. References
    23. Bonus Chapter 23. Advanced graphics with the lattice package
    24. Index
    25. List of Figures
    26. List of Tables
    27. List of Listings
    3.139.57.201