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Read it and master the invaluable art of solving data analysis problems efficiently: a must!
Built specifically for statistical computing and graphics, the R language, along with its amazing collection of libraries and tools, is one of the most powerful tools you can use to tackle data analysis for business, research, and other data-intensive domains. R in Action, Third Edition takes you hands-on with R, focusing on practical solutions and real-world applications that are most relevant to business developers. This revised and expanded third edition, covers the new tidyverse approach to data analysis and R’s state-of-the-art graphing capabilities with the ggplot2 package.
about the technology
The R language is the most powerful platform you can choose for modern data analysis. Free and open source, R’s community has created thousands of modules to tackle challenges from data-crunching to presentation. R’s graphical capabilities are also state-of-the-art, with a comprehensive and powerful feature set available for data visualization. R runs on all major operating systems and is used by businesses, researchers, and organizations worldwide.
about the book
R in Action, Third Edition teaches you to use the R language, including the popular tidyverse packages, through hands-on examples relevant to scientific, technical, and business developers. Focusing on practical solutions to real-world data challenges, R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualisations. In this revised and expanded third edition, new coverage has been added for R’s state-of-the-art graphing capabilities with the ggplot2 package.
A complete learning resource for R and tidyverse
Clean, manage, and analyze data with R
Use the ggplot2 package for graphs and visualizations
Techniques for debugging programs and creating packages
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
about the author
Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University, and a seasoned data scientist with more than 20 years of experience providing statistical programming and data analytic support in business, healthcare, and government settings. He has taught both undergraduate and graduate courses in data analysis and statistical programming and manages the Quick-R website at statmethods.net and the R for Data Visualization website at rkabacoff.github.io/datavis.
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