Response surface methodology is a statistical procedure used to understand, improve, and optimize a process.
Response surface methodology is a statistical procedure frequently used for optimization studies.
Meta-analysis is a statistical procedure that integrates the results of at least two independent studies.
Meta-analysis is a statistical procedure that integrates the result of several independent studies of similiar design.
PCA is a statistical procedure that transforms a number of possibly correlated variables into a smaller number of variables called principal components (Jolliffe 2002).
PCA is a statistical procedure that represents the original feature matrix in the principal component space with a view to producing a reduced number of principal components than the number of original features.
Design of experiments is a statistical procedure focused on detecting these links between the working variables and can reduce significantly the number of experiments, keeping, however, the reliability of the conclusions at a high standard.
The Bayesian method is a statistical procedure that allows the systematic incorporation and proper weighting of experimental data, prior knowledge of model and parameters, and probabilistic models of sources of experimental error.
PCA in fact is a statistical procedure used, not only in RS but in several fields of Science, to transform a set of correlated variables to a new set of uncorrelated variables (called components) that consider the principal directions in which the data are spread in the bands space.
While DIF is a statistical procedure to examine whether test items function differentially toward different groups of test takers who are matched on ability, fairness has a strong, subjective nature and is shaped by the particular social, economic, and political context where the test operates.
