the statistical multivariate analysis has a widespread use by researchers, creating a large demand for specific knowledge regarding its application concerning its assumptions and or limitations. in order to evaluate the degree of association among different characters of agronomic importance with an estimative reliable in biological terms, it is striking to quantify the multicolinearity among the studied variables. in addition, the types of statistical and mathematical models used in determining this linear dependence between classifying or independent variables may or may not be adequate for estimatives of biological parameters evaluated. the present work has as objective to present a critical evaluation on the degree of multicolinearity identified and evaluated on the path analysis performed on parts of a canola experiment. the results allow to postulate that path analysis application on the degree of severe multicolinearity produces results with no biological importance for the plant breeder. however, this limitation can be easily identified and corrected through path analysis with colinearity employing a constant (k) on diagonal axis of x？x matrix. the model of analysis with severe multicolinearity, however overestimated the single correlation coefficient values comparatively with the weak multicolinearity. even so, it may not be necessarily more precise, mainly regarding the evaluation of a restricted number of variables included in the analysis or an overlapping of the explainable variables.