It looks like you’re referring to the coefficient of variation (CV), which is calculated as follows:

$CV = \left( \frac{\text{Standard Deviation}}{\text{Mean}} \right) \times 100\%$

To calculate the CV for a specific data set, follow these steps:

1. Find the mean of the data set.
2. Find the standard deviation of the data set.
3. Divide the standard deviation by the mean.
4. Multiply the result by 100 to express it as a percentage.

If you can upload the data set or provide the sample data, I can walk you through the calculations step by step and give you the final CV rounded to the nearest tenth.

Would you like to upload the data or type it out?

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Here are 5 related questions you might explore after this:

1. How does the CV change when the data set’s mean increases but the standard deviation stays the same?
2. Can you use CV to compare data from different distributions effectively?
3. Why is the CV useful for comparing data sets with different units?
4. How does outlier data affect the standard deviation and, by extension, the CV?
5. In which fields or industries is the CV particularly useful for data analysis?

Tip: The coefficient of variation is particularly useful for comparing relative variability when the units of data differ significantly between two sets!