It's much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You'll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance. Anyone who wants to analyze data will find something useful here-even if you don't have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start. Get started with R by learning basic commands Build single variable graphs, such as dot and pie charts, box plots, and histograms Explore the relationship between two quantitative variables with scatter plots, high-density plots, and other techniques Use scatterplot matrices, 3D plots, clustering, heat maps, and other graphs to visualize relationships among three or more variables.

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Bibliographic Details

Title: Graphing Data with R
Publisher: O'Reilly Media
Publication Date: 2015
Language: English
ISBN 10: 1491922613
ISBN 13: 9781491922613
Binding: Paperback
Condition: Very Good

About this title

Synopsis

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance.

Anyone who wants to analyze data will find something useful here—even if you don’t have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start.

Get started with R by learning basic commands
Build single variable graphs, such as dot and pie charts, box plots, and histograms
Explore the relationship between two quantitative variables with scatter plots, high-density plots, and other techniques
Use scatterplot matrices, 3D plots, clustering, heat maps, and other graphs to visualize relationships among three or more variables

About the Author

John Jay Hilfiger is a statistician, with an MS in biostatistics. He has worked as a statistical/computer consultant in three major universities (Rochester, Iowa, Cornell). He has also made heavy use of his data background in positions as associate dean and as director of institutional research. In addition, Hilfiger is a composer/arranger (over 100 publications) and has been a music professor (masters and PhD in music). A big part of his experience has been helping other people analyze their data with numbers, graphs and insight; writing this book is an extension of that pursuit. He also has a

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