When would the range be particularly useful in data analysis?

The range is particularly useful in data analysis when a quick measure of dispersion is needed. It provides a straightforward way to understand how spread out the values in a dataset are by calculating the difference between the maximum and minimum values. This simplicity allows analysts to quickly gauge the extent of variability in the data without the need for complex calculations.

In scenarios where time is of the essence or when a rapid assessment is required, the range serves as an effective tool to identify the data's distribution, especially in smaller datasets. While it has its limitations, such as being sensitive to outliers and not providing detailed insights into the data's distribution shape, its ease of calculation makes it valuable for initial exploratory data analysis.

Other options may involve more complex statistical measures. For example, comparing averages requires different calculations and considerations, while assessing the total number of defects or determining standard deviation involves specific counts or calculations that provide deeper insights into variations or reliability but not the straightforward dispersion that the range provides.