Graphics for Statistics and Data Analysis with R

by Kevin J. Keen

Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.

489 pages, Hardcover

First published April 21, 2010

Reviews

[Vincentjones · Rating 4 out of 5]

I like the structure a lot. This books is organized by which type of data readers are dealing with:
A single discrete variable; a single continuous variable; two discrete variables; two continuous variables and more variables. This book also comes with advanced charts and regular charts two parts.