Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.