## 3 Results
### Analysis of Significance of Effects  
The analysis of effects was performed based on a multivariate analysis of variance. The analysis of variance was performed based on the classic linear model in the same way as in the single classification [42]. One of its results was the determination of the MSE error (mean square error) required to determine the subsequent contrasts and determine the random effect of the experiment (repeatability). The aforementioned analysis of effects was conducted based on a multifactor analysis of variance. The primary objective of such analysis was to determine the magnitude of the effects and to delineate contrasts amongst the array of combinations of the shovel amount and the PET additive in the concluded experiment. Initially, a verification of the assumptions of the analysis of variance was conducted. Consequently, preliminary normality tests were executed on the dependent variables: compressive strength after 28 and 56 days of curing and flexural strength after 28 and 56 days of mortar curing. The presence of outliers was also examined according to the Grubbs test procedure [42]. No outliers were identified within the analysed set. Additionally, all dependent variables for the Shapiro-Wilk test achieved a \(p\)-value > 0.05, providing no basis to reject the null hypothesis, which posits that the probability distribution of the results of the dependent variables conforms to a normal distribution. Upon satisfying the fundamental assumptions of the analysis of variance, its linear form, incorporating interaction components (cross-validation analysis), was used. In Table 5, the results of parameter significance are separately illustrated for each identified variable at a significance level of \(\alpha\) = 0.05. It is imperative to note that for all categories of mortar properties (dependent variables), both the quantity of glass and the amount of PET significantly impacted the variation in compressive and flexural strength after 28 and 56 days of the curing process of the mortar samples. Moreover, a multifactor effect size analysis was executed using the Shapiro-Wilk test. This analysis was conducted to ascertain the magnitude of the impact and to determine the level of explanation of the variability in the cumulative set of outcomes attributed to the dependent characteristics by the quantity of PET and glass. As a result, partial \(\eta^{2}\) was used, which is the quotient of the sum of squares attributed to the effect relative to the sum of squares of the given effect and the sum of ANOVA error squares [43]. As a \begin{table}
\begin{tabular}{c c c c c} \hline  & **Flexural Strength after** & **Compressive Strength** & **Flexural Strength after** & **Compressive Strength** \\  & **28 days [MPa]** & **after 28 days [MPa]** & **56 days [MPa]** & **after 56 days [MPa]** \\  & **(\(p\)-Value)** & **(\(p\)-Value)** & **(\(p\)-Value)** & **(\(p\)-Value)** \\ \hline Glass content [\%] & 0.0009 * & 1.3199 \(\times\) 10\({}^{-8}\) * & 0.2674 * & 2.41558 \(\times\) 10\({}^{-5}\) * \\ \hline PET content [\%] & 1.68 \(\times\) 10\({}^{-5}\) * & 0.0004 * & 0.0001 * & 0.0335 * \\ \hline Glass content [\%] \(\times\) & 0.4477 & 0.0952 & 0.8944 & 0.2194 \\ PET content [\%] & & & & \\ \hline \end{tabular}
\end{table} 
Table 5: ANOVA results for individual characteristics (effective hypothesis decomposition). result, the addition of glass explained 69% of the variation in the dependent variables studied, while the amount of PET explained 63% of their variation overall. Regarding the interaction between the quantities of PET and glass, the degree to which the variation in dependent characteristics is explained is merely 27%. Therefore, both dependent variables (the quantity of glass and the quantity of PET) elucidate the examined compressive and flexural strengths to a comparable degree. When evaluating the effects, it is sensible to illustrate the distribution of weighted means computed during the implementation of the ANOVA method algorithms.