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Because the relationships between PD and ln-CS are close to linear (see Additional File 2), these can be statistically compared by ANCOVA.
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The PCR and PLS models on the raw and first derivative spectra were statistically compared by ANOVA.
The results of these metrics were statistically compared by using the Wilcoxon rank-sum test.
The results of the groups were statistically compared by one-way ANOVA using post-hoc Bonferroni correction.
The result obtained on the synthetic mixture and tablets were statistically compared by the one-way ANOVA test.
The results were statistically compared by using 2-way ANOVA and the Tukey HSD post hoc test.
Two models were statistically compared by the coefficient of determination, root mean square error and absolute average deviation, based on the validation data set.
Both (RS Mand ANN) were statistically compared by the coefficient of determination, root mean square error and absolute average deviation, based on the validation data set.
Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set.
Objective noise indices were statistically compared by deriving the mean objective noise (SD of HU within ROI) at the ten measured levels for each data set.
Finally, the optimal solutions offered by RSM and ANN were statistically compared by the root mean square error (RMSE) and absolute average deviation (AAD) based on the validation data set.
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