R in Action Data analysis and graphics with R 2nd edition by Robert Kabacoff 9781638353331 1638353336

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Product details:

ISBN 10:1638353336
ISBN 13:9781638353331
Author:Robert Kabacoff
Summary
R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you’re likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide.
About the Book
R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

R in Action Data analysis and graphics with R 2nd  Table of contents:

Part 1. Getting started

Chapter 1. Introduction to R

Chapter 2. Creating a dataset

Chapter 3. Getting started with graphs

Chapter 4. Basic data management

Chapter 5. Advanced data management

Part 2. Basic methods

Chapter 6. Basic graphs

Chapter 7. Basic statistics

Part 3. Intermediate methods

Chapter 8. Regression

Chapter 9. Analysis of variance

Chapter 10. Power analysis

Chapter 11. Intermediate graphs

Chapter 12. Resampling statistics and bootstrapping

Part 4. Advanced methods

Chapter 13. Generalized linear models

Chapter 14. Principal components and factor analysis

Chapter 15. Time series

Chapter 16. Cluster analysis

Chapter 17. Classification

Chapter 18. Advanced methods for missing data

Part 5. Expanding your skills

Chapter 19. Advanced graphics with ggplot2

Chapter 20. Advanced programming

Chapter 21. Creating a package

Chapter 22. Creating dynamic reports

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