Factor loadings represent the correlation coefficients between observed variables and latent factors in factor analysis, indicating the degree to which each variable is associated with a particular factor. High factor loadings suggest that the variable is strongly influenced by the factor, making it crucial for interpreting the underlying structure of the data.

Factor Loadings

Factor loadings

correlation coefficients

Observed variables are measurable quantities in a study that researchers can directly assess and record, serving as the empirical basis for testing hypotheses and building models. They are contrasted with latent variables, which are not directly measurable and require indirect methods to be inferred from observed data.

observed variables

latent factors

Factor Analysis is a statistical method used to identify underlying relationships between variables by reducing the number of observed variables into a smaller number of latent factors. It helps in understanding the structure of data, simplifying datasets, and is widely used in fields like psychology, finance, and social sciences to uncover hidden patterns and dimensions.

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