Step 1 :First, we need to generate a normal probability plot for the given data and calculate the correlation coefficient of the plot. The correlation coefficient will tell us how closely the data follows a normal distribution. If the correlation coefficient is close to 1, it means the data is closely following a normal distribution. If it's far from 1, it means the data is not following a normal distribution.
Step 2 :We also need to find the critical value for the correlation coefficient. If the calculated correlation coefficient is greater than the critical value, we can conclude that the data comes from a normal population. Otherwise, we can't make that conclusion.
Step 3 :The given data is [0.155, 0.181, 0.206, 0.216, 0.226, 0.232, 0.24, 0.244, 0.249, 0.258, 0.277, 0.272, 0.292, 0.293, 0.321, 0.337].
Step 4 :The correlation coefficient is calculated to be approximately 0.996, which is very close to 1. This indicates that the data closely follows a normal distribution.
Step 5 :The critical value is approximately 1.96. Since the correlation coefficient is greater than the critical value, we can conclude that the data comes from a normal population.
Step 6 :Final Answer: \(\boxed{\text{Yes. The correlation between the expected z-scores and the observed data, 0.996, exceeds the critical value, 1.96. Therefore, it is reasonable to conclude that the data come from a normal population.}}\)