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Beginning R

An Introduction to Statistical Programming

  • Authors
  • Joshua F. Wiley
  • Larry A. Pace

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Joshua F. Wiley, Larry A. Pace
    Pages 1-13
  3. Joshua F. Wiley, Larry A. Pace
    Pages 15-25
  4. Joshua F. Wiley, Larry A. Pace
    Pages 27-34
  5. Joshua F. Wiley, Larry A. Pace
    Pages 35-42
  6. Joshua F. Wiley, Larry A. Pace
    Pages 43-52
  7. Joshua F. Wiley, Larry A. Pace
    Pages 53-65
  8. Joshua F. Wiley, Larry A. Pace
    Pages 67-72
  9. Joshua F. Wiley, Larry A. Pace
    Pages 73-80
  10. Joshua F. Wiley, Larry A. Pace
    Pages 81-92
  11. Joshua F. Wiley, Larry A. Pace
    Pages 93-100
  12. Joshua F. Wiley, Larry A. Pace
    Pages 101-110
  13. Joshua F. Wiley, Larry A. Pace
    Pages 111-120
  14. Joshua F. Wiley, Larry A. Pace
    Pages 121-137
  15. Joshua F. Wiley, Larry A. Pace
    Pages 139-161
  16. Joshua F. Wiley, Larry A. Pace
    Pages 163-192
  17. Joshua F. Wiley, Larry A. Pace
    Pages 193-213
  18. Joshua F. Wiley, Larry A. Pace
    Pages 215-277
  19. Joshua F. Wiley, Larry A. Pace
    Pages 279-301
  20. Joshua F. Wiley, Larry A. Pace
    Pages 303-320
  21. Back Matter
    Pages 321-327

About this book

Introduction

Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3.

R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics.  R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research.

What You Will Learn:

  • How to acquire and install R
  • Hot to import and export data and scripts
  • How to analyze data and generate graphics
  • How to program in R to write custom functions
  • Hot to use R for interactive statistical explorations
  • How to conduct bootstrapping and other advanced techniques

Bibliographic information