Correlation plots are a great tool to visualize correlation data. When two sets of data are related to one another, we say they are correlated. Hence, correlation can be negative, positive, or 0 (implying no correlation). The strength of the relationship can be defined by the correlation coefficient, which ranges from -1 (strong negative correlation) to 1 (strong positive correlation). What this implies is that when one series moves, the other series is most likely to move. The direction of the movement depends on the sign and the coefficient. Readers should note that correlation does not imply causation. Google Correlate allows its users to perform correlation on real world data.
R Data Visualization Cookbook
R Data Visualization Cookbook
Overview of this book
Table of Contents (17 chapters)
R Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
A Simple Guide to R
Basic and Interactive Plots
Heat Maps and Dendrograms
Maps
The Pie Chart and Its Alternatives
Adding the Third Dimension
Data in Higher Dimensions
Visualizing Continuous Data
Visualizing Text and XKCD-style Plots
Creating Applications in R
Index
Customer Reviews