To calculate the coefficient of variation (CV) for a set of data, we use the following formula:

$CV = \frac{\text{Standard Deviation}}{\text{Mean}} \times 100$

The steps to calculate the CV for each set are as follows:

Step 1: Mean and Standard Deviation for Set A

• Data for Set A: $2.2, 3.0, 4.4, 3.2, 1.8, 4.9, 4.2, 4.5, 2.8, 1.8, 1.5, 4.9, 4.8, 4.3$

Step 2: Mean and Standard Deviation for Set B

• Data for Set B: $21,603, 21,133, 22,072, 21,673, 21,797, 22,202, 21,385, 21,347, 21,311, 21,728, 22,284$

I'll now calculate the mean, standard deviation, and coefficient of variation for both sets.

Let me do the calculations.### Coefficient of Variation (CV) Results:

1. Set A:

   • Mean = 3.45
   • Standard Deviation = 1.27
   • Coefficient of Variation (CV) = 36.7%

2. Set B:

   • Mean = 21,685.0
   • Standard Deviation = 380.26
   • Coefficient of Variation (CV) = 1.8%

Would you like more details or have any questions?

Related Questions:

1. How is the standard deviation calculated for a dataset?
2. Why is the coefficient of variation used instead of standard deviation alone?
3. What does a higher CV indicate about a dataset?
4. Can the CV be used to compare datasets of different scales?
5. How would the CV change if the values in Set B were all doubled?

Tip: The coefficient of variation is helpful for comparing the relative variability between datasets, especially when the scales are different.