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  "body": "\n## Summary\n\nFactor analysis models many observed variables as linear combinations of a few unobserved common factors plus a noise term specific to each variable.\nIt is a [[latent variable model|C63RVH96TF]] that explains the correlations between the observed variables through the shared factors.\nThe model implies that the [[covariance matrix|0V7G6WMFK0]] is a low-rank matrix plus a diagonal matrix.\nIt is widely used in psychology and the social sciences.\n\n## Explanations\n\n### L1 human\n\nStudents who do well in algebra tend to do well in geometry, and good readers tend to be good writers.\nFactor analysis tries to explain such patterns by a few hidden abilities, for example a mathematical ability and a verbal ability.\nEach test score is then a weighted sum of the hidden abilities plus a part special to that test.\nThe weights, called loadings, show which tests depend on which abilities.\n",
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