Data Analysis with R

Author:   Garrett Grolemund
Publisher:   O'Reilly Media
ISBN:  

9781449359010


Pages:   300
Publication Date:   26 August 2014
Format:   Paperback
Availability:   In Print   Availability explained
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Data Analysis with R


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Overview

This guide is ideal if you're a professional, manager, or student who wants practical knowledge of analyzing data, without having to get a PhD in statistics. It's also good for people who have a PhD in statistics, but may not know how to write programs that apply statistical methods to real data. Discover how to apply the R language to data analysis through active learning and hands-on demonstration. You'll learn how to use R libraries that useful and reliable for data analysis, and how they can save you time and stress. Learn from a PhD-level statistician who develops and leads R courses Start analyzing data with R, rather than absorb academic statistics concepts Run more powerful analyses and make better-looking graphs Spend less time coding, with ggplot2, plyr, reshape2, and lubridate Learn how to make decisions during a data analysis

Full Product Details

Author:   Garrett Grolemund
Publisher:   O'Reilly Media
Imprint:   O'Reilly Media
Dimensions:   Width: 17.80cm , Height: 0.90cm , Length: 23.30cm
Weight:   0.413kg
ISBN:  

9781449359010


ISBN 10:   1449359019
Pages:   300
Publication Date:   26 August 2014
Audience:   Professional and scholarly ,  General/trade ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham's lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis.

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