The tests of normality overlay a normal curve on actual data, to assess the fit. A significant test means the fit is poor. For the standard alloy, the test is not significant; they fit the normal curve well. However, for the premium alloy, the test is significant; they fit the normal curve poorly.

Stem-and-leaf plots use the original data values to display the distribution's shape. The plot for premium bearings visualizes the positive skew statistic seen in the descriptives table; the values cluster uniformly in a range of 1530 to 1543 degrees, then disperse gradually at the higher temperatures.

Finally, a Q-Q plot is displayed. The straight line in the plot represents expected values when the data are normally distributed. The observed premium bearing values deviate markedly from that line, especially as temperature increases.