Canonical correlation analysis [CCA] is a multivariate statistical technique used to explore the relationship between two sets of variables. Canonical correlation is similar to correlation and regression, but it goes one step further by measuring the correlation of a linear combination of variables from each set that is maximally correlated with the linear combination of variables from the other set. Canonical correlation allows us to look at variables that are measured on different scales and identify the underlying relationship between them that can be used to explain their co-variation.

Correlation Matrix

All of that is a mouthful, but we can illustrate the technique in R using the

Create and print the correlation matrix

[corr_matrix