## 4 Results and Discussion  
### Results of the Initial Grouping of Source Data  
The first part of sorting the data was to group them according to the assumptions shown in Table 1. The results of grouping the data according to the adopted algorithm are shown in Table 2.  
The F statistic, given the truth of the null hypothesis, has an F Snedecor distribution with 8 degrees of freedom of the numerator and 20 degrees of freedom of the denominator. The empirical value of the statistic is F = 44.56, and the corresponding critical level of significance F = 4.413 \(\times\) 10\({}^{-11}\), which is less than the accepted significance level \(\alpha\) = 0.05. We therefore reject hypothesis H\({}_{0}\) in favor of H\({}_{1}\). There is no basis for rejecting the hypothesis that brake pad wear depends on at least one of the variables Xi = {X\({}_{1}\), X\({}_{2}\),\(\ldots\), X\({}_{8}\)}. We test the significance of the individual regression coefficients. The statistic at the truth of the null hypotheses has a Student's t-distribution with 20 degrees of freedom. The empirical values of the t-Student's statistic and the corresponding values of the critical level of significance (\(p\)-value) are shown in Table 4. There are no grounds for rejecting the hypothesis that the model constants \(\alpha_{i}=\{\alpha_{0}\),\(\ldots\),\(\alpha_{8}\}\backslash\{\alpha_{2}\),\(\alpha_{5}\}\) are insignificant, i.e., equal to zero (the values of the critical level of significance for these coefficients are greater than the accepted level of significance \(\alpha\) = 0.05). There is no basis for rejecting the hypothesis that the variables \(X_{i}=\{X_{1}\),\(\ldots\),\(X_{8}\}\backslash\{X_{2}\),\(X_{5}\}\) are insignificant. The current model structure is flawed. Re-Selection of the Linear Model Class  
For the new linear model, Formula (1) for \(X_{i}=\{X_{2}\),\(X_{5}\}\), model fitting was carried out at a significance level of \(\alpha\) = 0.05. The coefficient of the model is \(\overset{\sim}{\mathrm{R}^{2}}=0.927\) (coefficient of convergence \(\varphi^{2}\) = 6.8%). The model explains 92.7% of the variation in the studied trait. This shows a good fit of the model to the empirical data (Table 5). The F statistic, with the null hypothesis being true, has a Snedecor F distribution with 2 degrees of freedom of the numerator and 26 degrees of freedom of the denominator. The empirical value of the statistic is F = 178.177. The critical level of significance F = 6.65 \(\times\) 10\({}^{-16}\) is less than the accepted level of significance \(\alpha\) = 0.05. We therefore reject hypothesis H\({}_{0}\) in favor of H\({}_{1}\). There is no basis for rejecting the hypothesis that brake pad wear depends on at least one of the variables \(X_{i}=\{X_{2}\),\(X_{5}\}\). For each coefficient of the regression model \(\alpha_{i}\), we test the hypothesis of its significance. We verify it with a statistic of Student's t-distribution with 26 degrees of freedom. The empirical values of the t-Student's statistic and the corresponding values of the critical level of significance (\(p\)-value) are shown in Table 5. All the coefficients of the model are significantly different from zero (the values of the critical level of significance are less than the accepted level of significance \(\alpha\) = 0.05). There are no grounds for rejecting the hypothesis that all coefficients of the tested model