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R in action - Robert Kabacoff

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Title
R in action - data analysis and graphics with R
Author
Robert Kabacoff
format
Paperback / softback
Publisher
Manning Publications
Language
English
UK Publication Date
20110615

Description

Summary

R in Action is the first book to present both the R system and the use cases that make it such a compelling package for business developers. The book begins by introducing the R language, including the development environment.
Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.

About the Technology

R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.

About the Book

R in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually.

Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

What's Inside
  • Practical data analysis, step by step
  • Interfacing R with other software
  • Using R to visualize data
  • Over 130 graphs
  • Eight reference appendixes

================================

Table of Contents

    Part I Getting started
  1. Introduction to R
  2. Creating a dataset
  3. Getting started with graphs
  4. Basic data management
  5. Advanced data management
  6. Part II Basic methods
  7. Basic graphs
  8. Basic statistics
  9. Part III Intermediate methods
  10. Regression
  11. Analysis of variance
  12. Power analysis
  13. Intermediate graphs
  14. Re-sampling statistics and bootstrapping
  15. Part IV Advanced methods
  16. Generalized linear models
  17. Principal components and factor analysis
  18. Advanced methods for missing data
  19. Advanced graphics

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