Principal Component Analysis Calculator

Use the PCA Calculator to reduce a large number of correlating variables to a few independent latent variables, the so-called factors. The aim of the latent variables is to clarify as much of the variance of the original variables as possible. To carry out this dimensional reduction with your data, the following three steps are necessary:

• Copy your data into the table
• Select at least two variables
• Select the number of factors for the principal component analysis

Factor analysis calculator

The explorative factor analysis is a procedure that aims to uncover structures in large sets of variables. If you have a data set with many variables, it is possible that some of them are related, i.e. correlate with each other. These relationships (correlations) are the basis for factor analysis.