ABSTRACT
Correlation and multiple regression are very useful methods of statistical analysis. But often other advanced methods are needed to fully examine data. The most often applied other methods are exploratory factor analysis (EFA), cluster analysis, discriminant analysis, and partial least squares structural equation modeling (PLS-SEM). The appropriate research context for applying each of these methods is described. Suggested approaches for identifying and resolving potential problems in data analysis are summarized. Interpretation of the results is explained, including hypothesis testing.
