Weller S.C., Romney A.K. 1990, Metric Scaling. Correspondence Analysis, Newbury Park-London-New Delhi

Baxter M.J. 1994, Exploratory Multivariate Analysis in Archaeology, Edinburgh

Bendixen M. 1996, A Practical Guide to the Use of Correspondence Analysis in Marketing Research, in Marketing Research On-Line Vol. One -PDF-

Drennan R.D. 1996, Statistics for Archaeologist. A Commonsense Approach, New York

Shennan S. 1997, Quantifying Archaeology, Edinburgh (second edition)

Greenacre M. 2007, Correspondence Analysis in Practice, New York/London (second edition)

Micheloud F.X., Introduction to Correspondence Analysis, web document available at this link.

Yelland P.M., An Introduction to Correspondence Analysis, in The Mathematica Journal vol. 12 (available at this link).

Primer on Correspondence Analysis

Correspondence Analysis (CA) is a method of data analysis for representing tabular data graphically (Greenacre 2007: 1). Its graphical display potential is aimed to discover latent structure of the data and to facilitate complex data interpretation.
CA has been object of attention by archaeologist since it operate on data matrix. It is common in archaeological practice to build up, for several purposes, tables where contexts (e.g., tombs, huts, pits) are generally arranged in rows and their contents (e.g., vessels, bronze, pins, daggers, weights) in columns, while the table’s cells contain counts. This kind of practical arrangement of data is usually called contingency table. If we define contexts as objects and their contents as variables (for they can vary from a context to another), is can be said that a contingency table allows to display the joint distribution of variables between the objects. By this way, it is possible to make comparisons between objects, as far as their similarity in terms of variables is concerned [...]

See the full text of my Primer (pdf format).

For a more recent and extended version of my introduction to Correspondence Analysis, visit the site at this link.