Principal Axis Factoring (PAF) is a statistical method used in factor analysis to identify underlying relationships between observed variables by estimating common factors. Unlike other methods, PAF focuses on shared variance, making it suitable for exploring data structures when the assumption of normally distributed data is not strictly met.