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Model II in an RPL model with correlated parameters and interactions with SDC variables.
Significant single process parameters and interactions between them were determined through statistical analysis.
Furthermore, actions of parameters and interactions between parameters can be better understood using this method.
Table 2 presents the ANOVA of the data with the parameters and interactions significant for 95% confidence.
A factorial design was provide to evaluate the main parameters and interactions between the factors affecting the process of SBSE.
The analysis of variance was utilized to determine the level of significance of each process parameters and interactions.
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Open image in new window Fig. 12 Effect estimate of each uncertainty parameters and interaction of parameters on oil recovery.
Effect of parameters and interaction were analyzed using Pareto chart, main effect and interaction effect.
Post- versus prechanges of assessed parameters and interaction effects of "subjects" and "muscle" (SOL, VL) were assessed with a repeated ANOVA (Friedmann ANOVA).
The significances of each individual parameter and interaction parameter were estimated using a probability function analysis available in the software.
The admixture parameter and interaction parameter were initially set to α = 1 and ρ = 0.6, then automatically updated.
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