Canonical correlation is one of the procedures for explaining the relationship between the two sets of variates. The procedure is consisted of finding the linear combinations of variables that have the maximal correlation. The pairs that have the maximal correlation, but are not correlated with other linear combinations, are called canonical variates, while the correlation between the canonical variates is called the canonical correlation. Coefficients that maximize the correlation are the canonical coefficients. It is possible to study the relationship between the variables of the original vector and the canonical variate, where the obtained values are called canonical loadings. The correlation between variables of the original vector and the opposite canonical variate, which is called the canonical cross-loadings, can also be studied. As for the canonical correlations and canonical coefficients, they are obtained by the computing of eigenvalues and eigenvectors, so that the positive square roots of eigenvalue are canonical correlation, and eigenvectors are canonical coefficients. Given that the majority of data are not of the same variability, it is necessary to standardize them. Algebra used to calculate canonical coefficients and canonical correlations was also applied in the calculation of their estimates. The example included in this thesis studies the relationship between two variates. The first variate contains the psychological characteristics of the person, and the second is consisted of the academic characteristics. The first pair of canonical variates is used for the interpretation of the obtained results, since their correlation is the largest and statistically significant.