Tekijäanalyysiä
Tekijäanalyysiä, known in English as Factor Analysis, is a statistical method used to describe variability among observable, correlated variables in terms of a potentially smaller number of unobservable variables called factors. The primary goal of factor analysis is to reduce a large set of variables into a smaller, more manageable set of underlying dimensions or factors. This reduction can simplify complex data, reveal underlying structure, and help in theory development.
The core idea is that the observed correlations between variables can be explained by their shared relationship
There are two main types of factor analysis: exploratory factor analysis (EFA) and confirmatory factor analysis