Features

• Presents the fundamental principles of graphical data analysis
• Includes detailed case studies that explain how the principles can be applied to the analysis of real-world datasets, such as data on the city of Augsburg, the Titanic, olive oil, and the Tour de France
• Employs Mondrian software throughout to generate plots and provides some screenshots to illustrate certain techniques
• Uses R code to quantify results precisely, test statistical hypotheses, and rearrange data in a nontrivial way
• Provides exercises at the end of each chapter to critically review the topics discussed and address additional issues
• Offers course suggestions, slides, and extra code on the book’s website

Summary

Interactive Graphics for Data Analysis: Principles and Examples discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets.

Fundamentals of Interactive Statistical Graphics
The first part of the book summarizes principles and methodology, demonstrating how the different graphical representations of variables of a dataset are effectively used in an interactive setting. The authors introduce the most important plots and their interactive controls. They also examine various types of data, relations between variables, and plot ensembles.

Case Studies Illustrate the Principles
The second section focuses on nine case studies. Each case study describes the background, lists the main goals of the analysis and the variables in the dataset, shows what further numerical procedures can add to the graphical analysis, and summarizes important findings. Wherever applicable, the authors also provide the numerical analysis for datasets found in Cox and Snell’s landmark book.

Understand How to Analyze Data through Graphical Means
This full-color text shows that interactive graphical methods complement the traditional statistical toolbox to achieve more complete, easier to understand, and easier to interpret analyses.