Final answer:
To evaluate the normality of residuals, we would use a histogram. Although the given information suggests randomness with residuals centered on the regression line, supporting normality, without a histogram or additional statistical tests, we cannot conclusively determine if the residuals are normally distributed.
Step-by-step explanation:
The question asks whether the normality assumption is met for a set of residuals from a final regression equation. To assess this, we would typically construct a histogram of the residuals and analyze their shape. If the residuals are normally distributed, the histogram will approximate a bell-shaped curve, with most residuals clustered near the mean value and with similar frequencies of observations on either side of the mean. To evaluate the normality assumption using the given information, we look at several elements:
Assumption 1 states that the residuals should be centered on the line, indicating that the mean of the residuals should be close to zero if they are normally distributed. Given that the residuals are normally distributed about the regression line and the information suggests that there are no patterns indicating dependency, it would tentatively support the conclusion that the normality assumption may be met, but without the actual histogram or additional statistical tests, we cannot conclusively determine if the residuals are normally distributed. Please note that while the histogram is a visual tool to assess normality, it is often used in conjunction with other statistical tests to arrive at a more robust conclusion about the normality of the residuals.