Abstract
In the statistical treatment of measured data, factor analysis is often necessary. The methods involved can be used individually to emphasize the basic common factors in the group of variables; the factors produced can be then utilized as input data for other data analysis methods. The number of variables required to describe the system may be lowered, because the original variables may be correlated and, possibly, there is a smaller set of linearly independent variables. Thus, factor analysis is among the possible methods for the data analysis, when dealing with quantitative analytical measurements. Factor analysis of the measured data was used to lower the amount of variables in the analysis of steel; it was found that 94.5 % of the overall variance in the data can be attributed to three factors. Three original variables were assigned to these factors, lowering the number of required variables.