Learning R
(Sprache: Englisch)
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,...
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Klappentext zu „Learning R “
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
Inhaltsverzeichnis zu „Learning R “
- 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
Autoren-Porträt von Richard Cotton
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.
Bibliographische Angaben
- Autor: Richard Cotton
- 2013, 400 Seiten, mit Abbildungen, Maße: 17,9 x 23,1 cm, Kartoniert (TB), Englisch
- Verlag: O'Reilly Media
- ISBN-10: 1449357105
- ISBN-13: 9781449357108
- Erscheinungsdatum: 15.09.2013
Sprache:
Englisch
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