To calculate the coefficient of variation (CV) for the waiting times at Bank A, we need to follow these steps:

Step 1: Find the Mean of Bank A

The waiting times for Bank A are:
6.5, 6.6, 6.7, 6.8, 7.0, 7.3, 7.5, 7.6, 7.6, 7.7

The mean $\mu$ is calculated as: $\mu = \frac{6.5 + 6.6 + 6.7 + 6.8 + 7.0 + 7.3 + 7.5 + 7.6 + 7.6 + 7.7}{10}$

Step 2: Calculate the Standard Deviation (σ)

Now, we calculate the standard deviation using the formula: $\sigma = \sqrt{\frac{1}{n} \sum (x_i - \mu)^2}$ where $x_i$ are the individual waiting times and $\mu$ is the mean.

Step 3: Calculate the Coefficient of Variation (CV)

The coefficient of variation is given by: $CV = \left( \frac{\sigma}{\mu} \right) \times 100\%$ This gives us the percentage variation of the data relative to the mean.

Let me calculate these for you.

For Bank A:

• The mean waiting time is $7.13$ minutes.
• The standard deviation is $0.44$ minutes.
• The coefficient of variation (CV) is approximately 6.1%.

This means that the waiting times at Bank A vary by about 6.1% from the mean.

Would you like to calculate the CV for Bank B or need further details on the calculation?

Here are 5 related questions:

1. How do you calculate the coefficient of variation for Bank B?
2. What does a higher CV imply about the consistency of waiting times?
3. How is the standard deviation affected by more dispersed data?
4. Can the CV be used to compare different data sets with different units?
5. What is the difference between sample and population standard deviation?

Tip: The CV is useful for comparing the relative variability of data sets, especially when the means differ greatly.