## 3 Results and Discussion
### Analysis of Features
#### 3.3.1 Independent Samples Statistic
The analysis regarding the impact of data analysis tools on failure analysis suggests moderate evidence considering the positive impact on improving operational time, specifically MTBF. However, the diagnosticity of \(p\)-values using VS-MPR does not offer strong evidence favouring these findings, although the test statistic suggests significant results. Next, using LCM instruments in fault diagnosis, the analysis suggests a lack of solid evidence suggesting meaningful results. Although the parametric test statistic suggests significant results (\(p=0.037\)), the data are highly skewed, and the normality assumption is violated. Using the non-parametric Mann-Whitney test (\(p=0.238\)), the results suggest a lack of evidence supporting the effect. Lastly, using an expensive laboratorial analysis as a part of LCM practices, the biased sample and limited sample size suggest a lack of an effect measured by maintenance performance metrics. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metric** & **Test** & **Value** & \(p\) & **VS-MPR** & **SE Diff.** & **Effect** & **95\%CI\({}_{\text{L}}\)** & **95\%CI\({}_{\text{U}}\)** \\ \hline WOM & Student & \(-2.107\) & \(0.037\) & \(2.991\) & \(211.453\) & \(-0.430\) & \(-0.834\) & \(-0.025\) \\  & Welch & \(-1.722\) & \(0.092\) & \(1.676\) & \(258.605\) & \(-0.385\) & \(-0.791\) & \(0.026\) \\  & M-W. & \(1154\) & \(0.238\) & \(1.077\) & & \(-0.132\) & \(-0.350\) & \(0.099\) \\  & Student & \(0.962\) & \(0.338\) & \(1.003\) & \(0.509\) & \(0.196\) & \(-0.205\) & \(0.597\) \\  & Welch & \(0.858\) & \(0.395\) & \(1.000\) & \(0.571\) & \(0.185\) & \(-0.218\) & \(0.586\) \\  & M-W. & \(1663.5\) & \(0.032\) & \(3.312\) & \(0.251\) & \(0.024\) & \(0.453\) \\ MTBF & Student & \(-1.750\) & \(0.083\) & \(1.781\) & \(151.462\) & \(-0.357\) & \(-0.760\) & \(0.047\) \\  & Welch & \(-1.603\) & \(0.115\) & \(1.481\) & \(165.352\) & \(-0.341\) & \(-0.745\) & \(0.066\) \\  & M-W. & \(1118.5\) & \(0.180\) & \(1.192\) & & \(-0.159\) & \(-0.374\) & \(0.072\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Independent sample \(t\)-test statistic of LCMI. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metric** & **Test** & **Value** & \(p\) & **VSMPR** & **SE** & **Effect** & **95\%CI\({}_{\text{L}}\)** & **95\%CI\({}_{\text{U}}\)** \\ \hline WOM & Student & \(-2.706\) & \(0.008\) & \(9.612\) & \(598.316\) & \(-1.584\) & \(-2.747\) & \(-0.414\) \\  & Welch & \(-0.956\) & \(0.440\) & \(1.000\) & \(1693.95\) & \(-0.743\) & \(-2.016\) & \(0.645\) \\  & M-W. & \(98.50\) & \(0.225\) & \(1.096\) & & \(-0.392\) & \(-0.793\) & \(0.246\) \\ MTTR & Student & \(0.357\) & \(0.722\) & \(1.000\) & \(1.464\) & \(0.209\) & \(-0.939\) & \(1.356\) \\  & Welch & \(0.737\) & \(0.522\) & \(1.000\) & \(0.709\) & \(0.267\) & \(-0.924\) & \(1.411\) \\  & M-W. & \(181.5\) & \(0.726\) & \(1.000\) & \(0.12\) & \(-0.496\) & \(0.656\) \\ MTBF & Student & \(-0.817\) & \(0.416\) & \(1.000\) & \(438.694\) & \(-0.478\) & \(-1.626\) & \(0.672\) \\  & Welch & \(-0.475\) & \(0.681\) & \(1.000\) & \(754.619\) & \(-0.339\) & \(-1.491\) & \(0.883\) \\  & M-W. & \(131.0\) & \(0.579\) & \(1.000\) & & \(-0.191\) & \(-0.696\) & \(0.439\) \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Independent sample \(t\)-test statistic of LCML.