Graphical Data Analysis with R

See How Graphics Reveal Information

Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA.

Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

Table of Contents

Chapter 1: Setting the Scene
Chapter 2: Brief Review of the Literature and Background Materials
Chapter 3: Examining Continuous Variables
Chapter 4: Displaying Categorical Data
Chapter 5: Looking for Structure: Dependency Relationships and Associations
Chapter 6: Investigating Multivariate Continuous Data
Chapter 7: Studying Multivariate Categorical Data
Chapter 8: Getting an Overview
Chapter 9: Graphics and Data Quality: How Good Are the Data?
Chapter 10: Comparisons, Comparisons, Comparisons
Chapter 11: Graphics for Time Series
Chapter 12: Ensemble Graphics and Case Studies
Chapter 13: Some Notes on Graphics with
Chapter 14: Summary