factor analysis
the traits you weigh when considering someone for a task (Spearman)
Factor analysis is a statistical method used to identify patterns of relationship between a large number of observed variables and a smaller number of underlying, unobserved variables called factors. In simpler terms, it is a technique used to identify and understand the relationship between a large number of variables that are considered to be interrelated.
The goal of factor analysis is to identify the underlying factors that explain the observed variance in the variables being analyzed. It involves creating linear combinations of variables in order to explain as much of their variance as possible, and identifying the factors that are responsible for the most variance. Factors are usually interpreted as latent variables that capture a common theme among the variables they are composed of.
There are two main types of factor analysis: exploratory and confirmatory factor analysis. Exploratory factor analysis is used to identify the factors that are underlying a large set of variables, while confirmatory factor analysis is used to confirm the presence of a pre-specified set of factors.
Factor analysis is often used in fields such as psychology, sociology, marketing, and finance, in order to understand how complex sets of variables relate to each other. It is a powerful tool for identifying patterns of similarities and differences among variables, and for developing models that can capture these patterns in a meaningful way.
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