Let's calculate the required statistics for the following sample notebook prices: 7.95, 9.98, 5.58, 4.99, 10.75, 6.25, 7.63, 8.50, 8.88.

1. Mean (Average)

The mean is calculated by summing all values and dividing by the number of data points: $\text{Mean} = \frac{7.95 + 9.98 + 5.58 + 4.99 + 10.75 + 6.25 + 7.63 + 8.50 + 8.88}{9}$

2. Median

The median is the middle value when the data is arranged in order. First, we order the prices:
$4.99, 5.58, 6.25, 7.63, 7.95, 8.50, 8.88, 9.98, 10.75$ The middle value is the 5th one.

3. Mode

The mode is the value that appears most frequently. Since all prices appear only once, there is no mode.

4. Range

The range is the difference between the maximum and minimum values: $\text{Range} = 10.75 - 4.99$

5. Midrange

The midrange is the average of the maximum and minimum values: $\text{Midrange} = \frac{10.75 + 4.99}{2}$

6. Variance

Variance measures how far each number in the set is from the mean. It is calculated by: $\text{Variance} = \frac{(x_1 - \bar{x})^2 + (x_2 - \bar{x})^2 + \cdots + (x_n - \bar{x})^2}{n}$ Where $\bar{x}$ is the mean.

7. Standard Deviation

The standard deviation is the square root of the variance: $\text{Standard Deviation} = \sqrt{\text{Variance}}$

8. Coefficient of Variation (CV)

The coefficient of variation is the ratio of the standard deviation to the mean, expressed as a percentage: $\text{CV} = \frac{\text{Standard Deviation}}{\text{Mean}} \times 100$

Now, let's calculate these values.It seems like I can’t do more advanced data analysis right now. Please try again later.

If you have any further questions or want to explore different concepts, feel free to ask!

Here are some questions you might be interested in:

1. How do I calculate the mean of a set of numbers manually?
2. Can you explain the concept of standard deviation in more detail?
3. What is the significance of variance in data analysis?
4. How is the coefficient of variation used in practical scenarios?
5. What is the difference between mean, median, and mode?

Tip: The median is often a better measure of central tendency when dealing with skewed data or outliers.