## 3 Results
### Results of Statistical Analysis for the NiTi-2 Alloy
It can be seen from the figures  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Air**} \\ \hline
**Lower Bound** & **Upper Bound** & **Empirical PDF of \(\mathbf{c_{1}}\)** & \(f_{\mathbf{h}_{2}}^{(\mathbf{b})}\) & \(f_{\mathbf{h}_{3}}^{(\mathbf{l})}\) & \(f_{\mathbf{d}_{3}}^{(\mathbf{l})}\) \\ \hline
2 & 2.435 & 0.025 & 0.01385 & 0.02715 & 0.02134 \\ \hline
2.435 & 2.87 & 0.190 & 0.18738 & 0.19253 & 0.19026 \\ \hline
2.87 & 3.305 & 0.329 & 0.27879 & 0.24306 & 0.24657 \\ \hline
3.305 & 3.74 & 0.165 & 0.17412 & 0.18184 & 0.18053 \\ \hline
3.74 & 4.175 & 0.013 & 0.10563 & 0.11573 & 0.11574 \\ \hline
4.175 & 4.61 & 0.013 & 0.06723 & 0.07201 & 0.07337 \\ \hline
4.61 & 5.045 & 0.038 & 0.04466 & 0.04590 & 0.04758 \\ \hline
5.045 & 5.48 & 0.051 & 0.03073 & 0.03034 & 0.03182 \\ \hline
5.48 & 5.915 & 0.089 & 0.02179 & 0.02079 & 0.02195 \\ \hline
5.915 & 6.35 & 0.089 & 0.01585 & 0.01473 & 0.01557 \\ \hline \multicolumn{5}{c}{**Tide**} \\ \hline
**Lower Bound** & **Upper Bound** & **Empirical PDF of \(\mathbf{c_{1}}\)** & \(f_{\mathbf{h}_{2}}^{(\mathbf{l})}\) & \(f_{\mathbf{h}_{3}}^{(\mathbf{d})}\) & \(f_{\mathbf{h}_{2}}^{(\mathbf{g})}\) \\ \hline
0 & 2.3685 & 0.028 & 0.02283 & 0.02602 & 0.01590 \\ \hline
2.3685 & 4.737 & 0.097 & 0.11048 & 0.11122 & 0.13891 \\ \hline
4.737 & 7.1055 & 0.222 & 0.19252 & 0.18541 & 0.18772 \\ \hline
7.1055 & 9.474 & 0.264 & 0.19857 & 0.19567 & 0.17524 \\ \hline
9.474 & 11.8425 & 0.056 & 0.15321 & 0.15575 & 0.14199 \\ \hline
11.8425 & 14.211 & 0.028 & 0.10362 & 0.10700 & 0.10670 \\ \hline
14.211 & 16.5795 & 0.083 & 0.06723 & 0.06945 & 0.07647 \\ \hline
16.5795 & 18.948 & 0.069 & 0.04373 & 0.04480 & 0.05310 \\ \hline
18.948 & 21.3165 & 0.083 & 0.02900 & 0.02935 & 0.03601 \\ \hline
21.3165 & 23.685 & 0.069 & 0.01973 & 0.01969 & 0.02399 \\ \hline \multicolumn{5}{c}{**Sea**} \\ \hline
**Lower Bound** & **Upper Bound** & **Empirical PDF of \(\mathbf{c_{1}}\)** & \(f_{\mathbf{h}_{2}}^{(\mathbf{g})}\) & \(f_{\mathbf{h}_{3}}^{(\mathbf{d})}\) & \(f_{\mathbf{h}_{4}}^{(\mathbf{f})}\) \\ \hline
0 & 4.8685 & 0.000 & 0 & 0.00004 & 0.00011 \\ \hline
4.8685 & 9.737 & 0.014 & 0.00026 & 0.01563 & 0.01936 \\that the fitted distributions followed the empirical data well in both cases. The empirical data are unimodal, moderately right skewed, with a notable tail, especially in the case of exposing the alloy to an air influence. A similar graph can be formed for the influence of the sea on the corrosion rate in the case of the NiTi-2 alloy. From Figures 15 and 16 it is notable that the best-fitted theoretical distributions are positively skewed, i.e., skewed to the right. Based on this, it was concluded that a small number of corrosion rates would have high values. As a result, it was not surprising that the Log-Logistic and Burr distributions proved to be the most favourable, because they had the property of following the empirical data well, by which the most frequent events occurred at the beginning of the observed intervals. The lower and upper bounds of the intervals in Table 14 are the same as in Table 13, and were obtained by binning of the empirical data in ten equal-width intervals. Numerical results for the empirical CDFs were calculated based on the previously obtained empirical  
Figure 16: Empirical PDF and the three best fitted three-parameter distributions of the NiTi-2 alloy corrosion rate in a tidal environment. Figure 15: Empirical PDF and the three best fitted three-parameter distributions of the NiTi-2 alloy corrosion rate in the air environment. PDFs, while for calculation of the numerical results of the three best fitted theoretical three-parameter CDFs, the previously presented formulas were used, namely, Equations (34)-(36) for CDF functions describing the influence of air on the NiTi-2 alloy, Equations (40)-(42) for tidal influence and Equations (46)-(48) for the sea's influence.