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ICA is a statistical method to decompose multivariate data into statistically independent components (Calhoun et al., 2001; Beckmann and Smith, 2004; Hyvärinen et al., 2004).
The Taguchi method is a statistical method that utilizes the fundamental principles of statistics, randomization and replication for the design and analysis of factorial experiments.
Jackknifing is a statistical method to estimate the accuracy of sample statistics by repeatedly using subsets of available data to produce the results.
It is a statistical method of breaking a customer's requirements into tasks or steps, and setting the optimum specification for each part of the process, based on how the parts interact.
PCA is a statistical method that identifies patterns in data, revealing their similarities and differences [45].
SEM is a statistical method designed to test a conceptual or theoretical model (Kaplan 2007).
Factor analysis is a statistical method for discovering a basis/frame for a dataset.
The response surface method is a statistical method to model approximately and analyze the response surface.
It was validated with Response Surface Methodology (RS M, which is a statistical method.
Latent class analysis (LCA) is a statistical method for analyzing and understanding multivariate categorical data.
Meta-analysis is a statistical method used to aggregate data from independent studies.
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