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Learn about the early 20th-century attempt to define and measure intelligence through factor analysis, developed primarily by psychometrics scientists. Discover how the advent of computers generated renewed interest in this field, and why each application must be examined on its own merits. Explore the essence of factor analysis, its ability to describe covariance among variables in terms of underlying factors, and how it applies to examination scores. Delve into the orthogonal factor model, principal component solution, determination of the number of factors, and factor rotation.
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History Early 20th-century attempt to define and measure intelligence Developed primarily by scientists interested in psychometrics Advent of computers generated a renewed interest Each application must be examined on its own merits
Essence of Factor Analysis Describe the covariance among many variables in terms of a few underlying, but unobservable, random factors. A group of variables highly correlated among themselves, but having relatively small correlations with variables in different groups represent a single underlying factor
