\begin{tabular}{l} Part: \( 4 / 5 \) \\ Part 5 of 5 \\ Based on the results above, are the data approximately normally distributed \\ \begin{tabular}{|l|}\hline (Choose one) \( \nabla \) \\ \hline Yes \\ \hline\end{tabular} \\ \hline\end{tabular}

To determine if the data are approximately normally distributed, you can use a combination of quantitative and graphical methods. For example, creating a histogram or a Q-Q plot can help visualize the distribution. If the shape resembles a bell curve and the points on the Q-Q plot fall along a straight line, it's a good indication of normality. Another method is to perform statistical tests such as the Shapiro-Wilk test or the Kolmogorov-Smirnov test. Both tests assess the null hypothesis that the data is normally distributed. If the p-value from these tests is greater than a chosen significance level (commonly 0.05), you would fail to reject the null hypothesis, suggesting the data may be normal.