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.
Setting the Scene. Brief Review of the Literature and Background Materials. Examining Continuous Variables. Displaying Categorical Data. Looking for Structure: Dependency Relationships and Associations. Investigating Multivariate Continuous Data. Studying Multivariate Categorical Data. Getting an Overview. Graphics and Data Quality: How Good Are the Data?. Comparisons, Comparisons, Comparisons. Graphics for Time Series. Ensemble Graphics and Case Studies. Some Notes on Graphics with R. Summary. References. Indices.