In psychology, factor analysis is a mathematical way to reduce a large number of variables to a smaller number of variables for an experiment. The smaller number of variables are the ones that are actively reported at the conclusion of the experiment. Using factor analysis in experiments helps researchers find similarities between any variables that are being used.
Researchers use factor analysis to explain the results of tests and experiments. One example is the g factor experiment conducted by the British psychologist Charles Spearman, who is also credited with the invention of factor analysis. Spearman concluded that children who scored high on tests that assessed their verbal ability also did well on other tests that required the use of verbal skills. Spearman used factor analysis to correlate and isolate the factor that all of the tests had in common in order to reach his conclusion.
The drawback of using factor analysis for research is that it is only as good as the available data. In addition to this, factor analysis cannot identify causality, so the available data is often interpreted in a variety of ways. Factor analysis is most often used in intelligence research, although it is also used in other psychological studies, such as those dealing with personality, attitudes and beliefs.