Exploratory Factor Analysis -

: Numerical values representing the strength and direction of the relationship between an observed variable and a latent factor.

: The actual data collected, such as individual survey questions or test scores. Exploratory Factor Analysis

Exploratory Factor Analysis (EFA) is a multivariate statistical method used to uncover the underlying structure—or latent constructs—that explain correlation patterns between a set of observed variables. It is primarily used when researchers have no prior hypothesis about the data's nature and want to identify which variables group together to form common themes. : Numerical values representing the strength and direction

: Hidden variables that cannot be directly measured (e.g., "Intelligence" or "Extroversion") but influence the observable variables. It is primarily used when researchers have no

: Scores representing the amount of variance accounted for by each underlying factor. Factors with eigenvalues greater than 1.0 are often considered important.