Correspondence analysis (CA) is a quantitative data analysis method that offers researchers a visual understanding of relationships between qualitative (i.e., categorical) variables. Even though CA [Page 276]closely relates to the chi-square statistic (χ²), it is not an inferential method for directly testing theory and hypotheses. Instead, CA is a descriptive data reduction technique, similar to principal components analysis (PCA). Performing a CA using computer software offers researchers an easy way to interpret graphic representation of cross-tabulated data appearing in contingency tables. As widely used statistical methods seldom consider relationships between categorical variables, many such relationships go unnoticed in datasets. Although CA is a descriptive method, identification of any such previously unnoticed relationships can lead to future hypothesis testing. This entry provides background on the history ...