Factor analysis is a statistical technique that helps researchers identify relationships between variables. However, there are a number of synonyms for this term that serve the same purpose. Some of the most common include exploratory factor analysis, confirmatory factor analysis, principal component analysis, and latent variable analysis. Each of these techniques uses slightly different methods to examine data and identify underlying relationships among variables. Regardless of the specific technique used, all factor analytical approaches are designed to help researchers identify key factors that contribute to complex patterns of data. This information can be used to develop more accurate models, better predict outcomes, and gain deeper insights into the underlying causes of complex phenomena.