ABSTRACT

Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA and joint CA, translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social, environmental and health sciences, as well as marketing, economics, linguistics, archaeology, and more.

Michael Greenacre is Professor of Statistics at the Universitat Pompeu Fabra, Barcelona, Spain, where he teaches a course, amongst others, on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters, mostly on correspondence analysis, the latest being Visualization and Verbalization of Data in 2015. He has given short courses in fifteen countries to environmental scientists, sociologists, data scientists and marketing professionals, and has specialized in statistics in ecology and social science.

chapter 1|8 pages

Scatterplots and Maps

chapter 2|8 pages

Profiles and the Profile Space

chapter 3|8 pages

Masses and Centroids

chapter 4|8 pages

Chi-Square Distance and Inertia

chapter 5|8 pages

Plotting Chi-Square Distances

chapter 6|8 pages

Reduction of Dimensionality

chapter 7|8 pages

Optimal Scaling

chapter 8|8 pages

Symmetry of Row and Column Analyses

chapter 9|8 pages

Two-Dimensional Displays

chapter 10|8 pages

Three More Examples

chapter 11|8 pages

Contributions to Inertia

chapter 12|8 pages

Supplementary Points

chapter 13|8 pages

Correspondence Analysis Biplots

chapter 14|8 pages

Transition and Regression Relationships

chapter 15|8 pages

Clustering Rows and Columns

chapter 16|8 pages

Multiway Tables

chapter 17|8 pages

Stacked Tables

chapter 18|8 pages

Multiple Correspondence Analysis

chapter 19|8 pages

Joint Correspondence Analysis

chapter 20|8 pages

Scaling Properties of MCA

chapter 21|8 pages

Subset Correspondence Analysis

chapter 22|8 pages

Compositional Data Analysis

chapter 23|8 pages

Analysis of Matched Matrices

chapter 24|8 pages

Analysis of Square Tables

chapter 25|8 pages

Correspondence Analysis of Networks

chapter 26|8 pages

Data Recoding

chapter 27|8 pages

Canonical Correspondence Analysis

chapter 28|8 pages

Co-Inertia and Co-Correspondence Analysis

chapter 29|8 pages

Aspects of Stability and Inference

chapter 30|8 pages

Permutation Tests