Final answer:
Outliers are more easily identifiable in a boxplot compared to a stem-and-leaf plot. The boxplot visually represents potential outliers based on the interquartile range, which is not as apparent in a stem-and-leaf plot.
Step-by-step explanation:
One feature of the data that is seen in the boxplot that is not easily seen in the stem-and-leaf plot is outliers. The boxplot is constructed from five key values: the minimum value, the first quartile, the median, the third quartile, and the maximum value. It gives a clear and immediate visual representation of the potential outliers, which are data points that fall outside the expected range based on the interquartile range (IQR). Outliers are typically identified as points that lie more than 1.5 times the IQR below the first quartile or above the third quartile.
While median, quartiles, and range can be determined from both, the boxplot provides a better visual indication of outliers. This can be helpful for quickly spotting and considering the impact of these values on the data set.