A01=John Jay Hilfiger
analysis
analysis of variance
Author_John Jay Hilfiger
Category=UFM
data
data analysis
data modelling
data visualization
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
ggplot2
graphics
informatics
r
r packages
statistics
variance
visualization
Product details
- ISBN 9781491922613
- Weight: 486g
- Dimensions: 153 x 230mm
- Publication Date: 08 Dec 2015
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
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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
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.
