What does factor loading represent in factor analysis?

• A. The correlation between individual variables and factors
• B. The overall fit of the model
• C. The average variance explained by each factor
• D. The total number of factors extracted

Answer: (A)

Factor loading represents the correlation between individual variables and factors, which indicates how much a variable is influenced by a particular factor, or how much that factor contributes to explaining the variance of the variable. In factor analysis, each variable is associated with one or more factors through these loadings. High factor loadings suggest that the variable is strongly related to the factor, whereas low loadings indicate a weaker relationship. This measure is essential for interpreting the data and understanding the underlying structure represented by the factors.

The overall fit of the model, which is more aligned with the goodness-of-fit measures, assesses how well the model represents the data but does not directly relate to individual variables. The average variance explained by each factor addresses how much variability in the dataset is accounted for by a factor as a whole, rather than the relationship of individual variables to the factor. The total number of factors extracted refers to the number of distinct factors identified in the analysis, which does not convey the strength of the relationship between those factors and the variables. Thus, the first choice clearly captures what factor loading signifies in the framework of factor analysis.