Consider the following sets of sample data:

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
B:  	21,603, 21,133, 22,072, 21,673, 21,797, 22,202, 21,385, 21,347, 21,311, 21,728, 22,284

Step 1 of 2 :  For each of the above sets of sample data, calculate the coefficient of variation, CV. Round to one decimal place.

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.

For each of the above sets of sample data, calculate the coefficient of variation, CV. Round to one decimal place.

Learn how to calculate the coefficient of variation (CV) for two sets of sample data A and B. This problem includes calculating the mean, standard deviation, and CV to understand data variability. Suitable for students in Grades 10-12.

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