Exploratory Factor Analysis
Exploratory Factor Analysis (EFA) is a statistical method used to identify underlying factors or latent variables that explain the correlations among a set of observed variables. EFA is a data reduction technique that aims to simplify a large dataset by identifying patterns and relationships among variables. It is commonly used in social sciences, psychology, and marketing research to identify the underlying constructs that influence human behavior. EFA assumes that the observed variables are influenced by a smaller number of unobserved factors, and it seeks to identify these factors and their relationships with the observed variables. EFA can be used to identify the number of factors that best explain the data, to determine which variables are most strongly related to each factor, and to assess the reliability and validity of the measurement instruments used to collect the data.
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