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

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

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


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
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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
Citeste mai mult

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