## 3 Results
### Results of Statistical Analysis for the NiTi-2 Alloy
In other words, three empirical data sets for the corrosion rate of the NiTi-1 alloy were compared, and then another group of tests was performed to compare the empirical data for air, tide and sea effects in the case of the NiTi-2 alloy. As the assumption of the normality of the empirical data for NiTi alloys is not acceptable (see Section 3. Figure 7), the Kruskal-Wallis test [60] was used for the comparison of independent samples. The Kruskal-Wallis test is an alternative test for comparing independent samples in the case when the normality of the data cannot be determined. In this paper, the Kruskal-Wallis test was used to compare the empirical results for the behaviour of the NiTi-1 alloy in air, tide and sea. Also, the same test was employed to compare the empirical data related to the corrosion rate of the NiTi-2 alloy in the air, tide and sea environments. Namely, three groups of samples were compared together, to determine whether they came from the same population, or populations with the same position parameter. Therefore, the following hypotheses were set:  
**H0. **\(P_{p1}=P_{p2}=\ldots=P_{pk}\) (_i.e., the samples came from the same population_). **Ha. **_There is at least one pair \((i,j)\) such that \(P_{pi}\
eq P_{pj}\) (i.e., the samples did not come from the same population)._  
where \(P_{pi}\) represents the position parameter of the sample \(i\). Figure 17: Empirical PDF and the three best fitted three-parameter distributions of NiTi-2 alloy corrosion rate in the sea environment. A significance level \(\alpha=0.05\) was used In all Kruskal-Wallis tests. Test statistics and the corresponding critical value were calculated, as well as the corresponding \(p\)-value for the assumed level of significance. Based on the Kruskal-Wallis tests and the empirical data obtained based on the air, tide and sea influence on the NiTi-1 alloy corrosion rate, the three sample groups showed statistically different characteristics. Namely, in the case of comparative statistical analysis of three groups of empirical data related to the behaviour of the NiTi-1 alloy in a seawater environment, the obtained test statistic was 124.71, the critical value was 5.99 and the related \(p\)-value was lower than 0.0001. As the computed \(p\)-value was lower than the significance level \(\alpha=0.05\), the null hypothesis H0 cannot be accepted. By comparing three groups of empirical data related to the behaviour of the NiTi-2 alloy and applying the Kruskal-Wallis test, it was found that there were statistically significant differences in the empirical data of these three groups of measured values of corrosion rate. An identical conclusion can be drawn based on the application of the Kruskal-Wallis test to empirical data related to the influence of air, tide, and sea in the case of the NiTi-2 alloy, as in the case of NiTi-1 alloy. Based on the Kruskal-Wallis procedure for testing the statistical hypothesis H0, a test statistics value of 155.42 was obtained, a critical value of 5.99 was determined, and the corresponding \(p\)-value was lower than 0.0001. Based on these values, it was concluded that the alternative hypothesis Ha was accepted, because the \(p\)-value was lower than the significance level \(\alpha\). In this case, the risk to reject the null hypothesis H0 while it was true, was again lower than 0.01%. The Kruskal-Wallis test can only answer the question of whether differences between the observed data groups exist or not, but it cannot detect which data group is the one that causes the rejection of the null hypothesis. To overcome this problem, it is necessary to apply post hoc tests. Multiple comparison procedures, known as the Steel-Dwass-Critchlow-Figner two-tailed test [61], were used in this paper. This method of comparison was proposed by [PERSON] [62], and is based on the calculation of \(W_{ij}\) statistics. More precisely, the \(W_{ij}\) statistic value is recalculated for each combination of together ranked groups of samples.