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

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

Learning R : A Step-By-Step Function Guide to Data Analysis Paperback - 2013

by Richard Cotton

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O'Reilly Media, Incorporated, 2013. Paperback. Good. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.Dust jacket quality is not guaranteed.
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Details

  • Title Learning R : A Step-By-Step Function Guide to Data Analysis
  • Author Richard Cotton
  • Binding Paperback
  • Edition INTERNATIONAL ED
  • Condition Used - Good
  • Pages 396
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media, Incorporated, n
  • Publication date 2013
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # G1449357105I3N00
  • ISBN 9781449357108 / 1449357105
  • Weight 1.43 lbs (0.65 kg)
  • Dimensions 9.18 x 7.1 x 0.82 in (23.32 x 18.03 x 2.08 cm)
  • Category Computers - Languages / Programming
  • Library of Congress subjects Statistics - Data processing, R (Computer program language)
  • Dewey Decimal Code 519.502
  • Quantity available 2

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From the publisher

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

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.

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