Learning R: A Step-by-Step Function Guide to Data Analysis

Learning R: A Step-by-Step Function Guide to Data Analysis

by Richard Cotton
Learning R: A Step-by-Step Function Guide to Data Analysis

Learning R: A Step-by-Step Function Guide to Data Analysis

by Richard Cotton

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Overview

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.

The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code.

  • Write a simple R program, and discover what the language can do
  • Use data types such as vectors, arrays, lists, data frames, and strings
  • Execute code conditionally or repeatedly with branches and loops
  • Apply R add-on packages, and package your own work for others
  • Learn how to clean data you import from a variety of sources
  • Understand data through visualization and summary statistics
  • Use statistical models to pass quantitative judgments about data and make predictions
  • Learn what to do when things go wrong while writing data analysis code

Product Details

ISBN-13: 9781449357108
Publisher: O'Reilly Media, Incorporated
Publication date: 09/30/2013
Pages: 396
Sales rank: 750,352
Product dimensions: 6.90(w) x 9.00(h) x 0.90(d)

About the Author

Richie is a data scientist with a background in chemical health and safety, and has worked extensively on tools to give non-technical users access to statistical models. He is the author of the R packages "assertive" for checking the state of your variables and "sig" to make sure your functions have a sensible API. He runs The Damned Liars statistics consultancy.

Table of Contents

  • Preface
  • The R Language
    • Chapter 1: Introduction
    • Chapter 2: A Scientific Calculator
    • Chapter 3: Inspecting Variables and Your Workspace
    • Chapter 4: Vectors, Matrices, and Arrays
    • Chapter 5: Lists and Data Frames
    • Chapter 6: Environments and Functions
    • Chapter 7: Strings and Factors
    • Chapter 8: Flow Control and Loops
    • Chapter 9: Advanced Looping
    • Chapter 10: Packages
    • Chapter 11: Dates and Times
  • The Data Analysis Workflow
    • Chapter 12: Getting Data
    • Chapter 13: Cleaning and Transforming
    • Chapter 14: Exploring and Visualizing
    • Chapter 15: Distributions and Modeling
    • Chapter 16: Programming
    • Chapter 17: Making Packages
  • Appendixes
  • Bibliography
  • Index
  • Colophon
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