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By reducing data, this technique is used to explain the variability among observed variables in terms of a smaller number of non-observed variables called factors.
Factor analysis is a statistical method used to describe variability among observed variables in terms of fewer unobserved variables called factors [ 22].
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.
This is a statistical method used to describe variability among observed, correlated, variables in terms of a potentially lower number of unobserved variables (called factors).
FA [27, 28] is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.
On the other hand, FA is a statistical data reduction technique used to explain variability among observed random variables in terms of fewer unobserved random variables called factors.
Factor analysis is a statistical method that describes variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors [ 16].
The dispersion coefficients of particles were well correlated with operating variables in terms of dimensionless groups.
Additionally, it is capable of handling both qualitative and quantitative variables in terms of probability.
The theory manages to map the electronic variables in terms of which the problem is originally posed to the Composite Fermion variables that describe the ultimate quasiparticles.
When explaining job satisfaction, research usually focuses on predictor variables in terms of levels but neglects growth rates.
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CEO of Professional Science Editing for Scientists @ prosciediting.com