ABSTRACT
Factor Analysis attempts to simplify a large body of data by identifying or discovering redundancy in the data. The factors are smaller representations that are derived from a larger matrix of correlations. In psychological research intercorrelations among a set of tests, such as the subtests of Wechsler Intelligence Scale for Children (WISC), reveal groups of subtests that are interrelated. The elements of a factor are the correlations of each test with the factor, called factor loadings. The factor loadings can derive meaning from basic assumptions surrounding test scores. The total variance of the scores on a test or variable may also be subdivided into three general types - common, specific, and error variance. Common variance is that portion of the total variance that correlates with other variables. Unique variance is the sum of specific variance and error variance. Error variance is chance or random variance, due to errors of sampling, measurement.
