# Evaluation of Impact Energy Absorption by Natural Fiber Composites in Motorcycle Helmets
## 4 Results and Discussion  
The data obtained from the impact energy absorption test were subjected to the Shapiro-Wilk test to assess the normality of the polyurethane foam (PU) and the composites reinforced with natural fiber prototypes. Hypothesis testing was conducted using R-Studio, a widely used tool for statistical analyses. The p-values obtained were considered to evaluate the normality of the distribution; a distribution was deemed normal when the p-value exceeded 0.05. The following hypotheses were formulated to assess the data distributions: H0: there is statistical evidence that the data are normally distributed; H1: there is no statistical evidence that the data are normally distributed. Table 3 presents the test results, which provide insights into the adequacy of the data distribution concerning the normality assumption. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Type and Quantity of Fiber** & \(p\)**-Value** & **Conclusion** \\ \hline PU 0\% & 0.575 & There is no evidence to reject the null hypothesis \\ Sugarcane bagasse 5\% & 0.929 & There is no evidence to reject the null hypothesis \\ Coconut 5\% & 0.655 & There is no evidence to reject the null hypothesis \\ Agave sisalana 5\% & 0.086 & There is no evidence to reject the null hypothesis \\ Sugarcane bagasse 10\% & 0.940 & There is no evidence to reject the null hypothesis \\ Cooconut 10\% & 0.605 & There is no evidence to reject the null hypothesis \\
**Agave sisalana 10\%** & **0.018** & **One has evidence to reject the null hypothesis** \\ Sugarcane bagasse 15\% & 0.238 & There is no evidence to reject the null hypothesis \\ Coconut 15\% & 0.588 & There is no evidence to reject the null hypothesis \\ Agave sisalana 15\% & 0.238 & There is no evidence to reject the null hypothesis \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Shapiro-Wilk for free-fall results. The results presented in Table 3 were evaluated at a 5% significance level. The null hypothesis, H0, was rejected for the 10% sisal dataset, in bold, indicating that it does not follow a normal distribution. In contrast, the null hypothesis was not rejected for the other datasets, suggesting they may approximate a normal distribution. Based on these findings, outliers were addressed. [PERSON]'s criterion was applied to the datasets that exhibited a normal distribution. At the same time, the interquartile range (IQR) method was used for the dataset where the null hypothesis was rejected. The outcomes of these analyses are shown in Tables 4 and 5. According to the results presented in Table 4, applying [PERSON]'s criterion revealed outliers in the sisal sample sets with 5% and 15% concentrations. These outliers were excluded from the analysis, as their presence could negatively impact the results and hinder the accurate interpretation of the data. The interquartile range (IQR), defined as the difference between the third quartile (Q3) and the first quartile (Q1), serves as a measure of dispersion for the central half of the observed data. One used IQR to establish lower and upper thresholds for effective outlier detection. As outlined in Table 5, an outlier was identified in the dataset containing 10% Agave sisalana, with a value of 75.40. This atypical value was promptly excluded from subsequent analyses to ensure accurate interpretation and sound conclusions regarding the results. After this outlier was excluded, the modified dataset underwent the Shapiro-Wilk test to evaluate its normality. This step was undertaken due to concerns that the outlier might have distorted our understanding of the data's distribution. One employed a 5% significance level for this test, and the hypotheses evaluated were as follows: H0: there is statistical evidence that the data are normally distributed; H1: there is no statistical evidence that the data are normally distributed. The results of this test are presented in Table 6.