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. Ž . Principal component analysis PCA was performed on a data matrix consisting of eight polarity indicators scales and 30 stationary phases. Calculations were carried out on the correlation matrices of values characterizing polarityrselectivity Ž . of liquid phases columns . It was found that three principal components account for more than 99% of the total variance in the data, indicating that no single polarity variable is applicable on alone. The plots of component loadings and component scores showed significant groupings of polarity indicators and of stationary phases, respectively. The polarity indicators can Ž . be divided into two groups: i the sum of the first five McReynolds constants, Kovats' coefficients, Castello's DC values; Ž . ii Snyder's selectivity parameters. The latter differ from each other and from the other polarity indicators considerably. The Ž physical meaning attributed to the most influential abstract factors, are as follows: Factor 1, polarity according to . McReynolds, Kovats and Castello ; Factor 2, hydrogen donating and accepting ability; Factor 3, dipole interactions. Sequen-tial analyses showed that polarity represents a nonlinear function among the phases.