Exploratory factor analysis is a statistic procedure used to determine, under the condition of underlying latent constructs which may influence the variables, the relationships among variables and dimensions. Factor analysis determines which factors best fit the data and thereby serve to validate the data, but this process is only applicable when there are relationships among variables and when researchers are testing a large sample size. Alternative: Exploratory factor analysis involves first collecting data without first postulating anything before analysis, then finding a measurement model that best fits the data collected. Exploratory factor analysis may result in an infinite number of equally likely solutions.
Morgan, G. A., Leech, N. L., Gloeckner, G. W., and Barrett, K. C. (2013). IBM SPSS for introductory statistics: Use and interpretation. New York, NY: Routledge.