Discrete Data Analysis With R ─ Visualization and Modeling Techniques for Categorical and Count Data

The special nature of discrete variables and frequency data vis-a-vis statistical graphics is now more widely accepted, and many of these methods (e.g., mosaic displays, fourfold plots, diagnostic plots for generalized linear models) have become, if not main stream, then at least more widely used in research and teaching. This book provides an accessible introduction to the major methods of categorical data analysis for data exploration, statistical testing and statistical models. As opposed to more theoretical books, the goal here is to help the reader to translate theory into practical application, by providing skills and software tools for carrying out these methods.

Michael Friendly is a professor of psychology, founding chair of the Graduate Program in Quantitative Methods, and an associate coordinator with the Statistical Consulting Service at York University. He earned a PhD in psychology from Princeton University, specializing in psychometrics and cognitive psychology. In addition to his research interests in psychology, Professor Friendly has broad experience in data analysis, statistics, and computer applications. His main research areas are the development of graphical methods for categorical and multivariate data and the history of data visualization. He is an associate editor of theJournal of Computational and Graphical Statistics and Statistical Science.

David Meyer is a professor of business informatics at the University of Applied Sciences Technikum Wien. He earned a PhD in business administration from the Vienna University of Economics and Business, with an emphasis on computational economics. Dr. Meyer has published numerous papers in various computer science and statistical journals. His research interests include R, business intelligence, data mining, and operations research.