Answer
The data set does not show normality.
Please see below for explanations.
Work Step by Step
1. As shown in the figure, we first construct a frequency distribution and draw a histogram for the data.
Clearly the histogram is strongly right skewed and it is not bell-shaped.
2. We use the Pearson coefficient (PC) to check for skewness. The mean is $\bar X=970.2$, median=$853.5$,
standard deviation $s=376.5$. So $PC=\frac{3(970.2-853.5)}{376.5}=0.93$, this number is close to 1 indicating
that the distribution is strongly skewed.
3. We check for outliers to see if any data lie outside $\pm1.5IQR$ of the mean. IQR can be found as 95 and
1.5IQR=132.5 giving a range of $\bar X-1.5IQR=837.7$ to $\bar X+1.5IQR=1102.7$
compare the data to this range, we found that 2084 1497 826 815 750 637 737 are outliers.
Conclusion, the histogram does not show a bell-shaped distribution, the Pearson coefficient is close to 1
indicating a strongly right skewed distribution, and there are many outliers in the data set.
The data set does not show normality.
