## Canonical correlation analysis, Applied Statistics

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Canonical correlation analysis (CC) allows the investigation of the relationship between two ,sets of variables. For example, a sociologist may want to investigate the Relationship between two predictors of social mobility based on interviews, with actual subsequent social nlobility as measured by four different indicators. A medical researcher may want to study the relationship of various risk factors to the development of a group of symptoms. In all of these cases, the researcher is interested in the relationship betweet; ' two, sets of variables, and Canonical Correlation would be the appropriate method of analysis. . Canonical Correlation combines the dependent variables to find pairs, of new variables called canonical variables, CV, 'one for each data table having the highest . correlation. However, the CV's, even when highly correlated, do not necessarily explain a large portion of the variance of the original tables. This makes the interpretation of the CV sometimes difficult, but CC is nonetheless an important theoretical tool because most multivariate techniques can be interpreted as a special case of CC.

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