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R In Action Data Analysis And Graphics With R Additional Materials 2nd Edition Kabacoff Ri

  • SKU: BELL-6606676
R In Action Data Analysis And Graphics With R Additional Materials 2nd Edition Kabacoff Ri
$ 31.00 $ 45.00 (-31%)

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R In Action Data Analysis And Graphics With R Additional Materials 2nd Edition Kabacoff Ri instant download after payment.

Publisher: Manning Publications
File Extension: RAR
File size: 1.25 MB
Author: Kabacoff R.I.
Language: English
Year: 2015
Edition: 2

Product desciption

R In Action Data Analysis And Graphics With R Additional Materials 2nd Edition Kabacoff Ri by Kabacoff R.i. instant download after payment.

2nd Edition. — Manning Publications, 2015. — 608 p. — ISBN: 978-1617291388.
Bonus chapter 23 and source code from this book placed here.
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.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.What's inside:
Complete R language tutorial;
Using R to manage, analyze, and visualize data;
Techniques for debugging programs and creating packages;
OOP in R;
Over 160 graphs.About the reader:
This book is designed for readers who need to solve practical data analysis problems using the R language and tools. Some background in mathematics and statistics is helpful, but no prior experience with R or computer programming is required.

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