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

� propos de l?auteur

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.

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