The frequency distribution of a data set is a summary of the frequency of individual values or ranges of values in the data. Here's how you can create a frequency distribution for the given data set:

1. First, you need to identify the range of the data. In this case, the usage rates range from 0.10% to 87.30%.

2. Next, you need to decide on the number of classes or intervals for your frequency distribution. This can be arbitrary, but a common rule of thumb is to take the square root of the number of data points. In this case, there are 44 data points, so you might choose to have around 7 classes.

3. Then, you need to calculate the width of each class. This is done by subtracting the lowest value from the highest value and dividing by the number of classes. In this case, (87.30 - 0.10) / 7 = 12.46, so each class might be 12.46% wide.

4. Now, you can create a table with the classes in one column and the frequency in another. For each character, you would determine which class their usage rate falls into and increase the frequency for that class by one.

5. Finally, you can calculate the relative frequency for each class by dividing the frequency by the total number of data points. This gives you the proportion of the data that falls into each class.

Here's an example of what the frequency distribution might look like:

| Class Interval | Frequency |
|----------------|-----------|
| 0.10 - 12.56 | 16 |
| 12.57 - 25.03 | 5 |
| 25.04 - 37.50 | 4 |
| 37.51 - 49.97 | 3 |
| 49.98 - 62.44 | 5 |
| 62.45 - 74.91 | 6 |
| 74.92 - 87.30 | 5 |

This is a simplified example and the actual frequency distribution might look slightly different depending on the exact class intervals you choose.

Question

The frequency distribution of a data set is a summary of the frequency of individual values or ranges of values in the data. Here's how you can create a frequency distribution for the given data set:

1. First, you need to identify the range of the data. In this case, the usage rates range from 0.10% to 87.30%.

2. Next, you need to decide on the number of classes or intervals for your frequency distribution. This can be arbitrary, but a common rule of thumb is to take the square root of the number of data points. In this case, there are 44 data points, so you might choose to have around 7 classes.

3. Then, you need to calculate the width of each class. This is done by subtracting the lowest value from the highest value and dividing by the number of classes. In this case, (87.30 - 0.10) / 7 = 12.46, so each class might be 12.46% wide.

4. Now, you can create a table with the classes in one column and the frequency in another. For each character, you would determine which class their usage rate falls into and increase the frequency for that class by one.

5. Finally, you can calculate the relative frequency for each class by dividing the frequency by the total number of data points. This gives you the proportion of the data that falls into each class.

Here's an example of what the frequency distribution might look like:

| Class Interval | Frequency |
|----------------|-----------|
| 0.10 - 12.56   | 16        |
| 12.57 - 25.03  | 5         |
| 25.04 - 37.50  | 4         |
| 37.51 - 49.97  | 3         |
| 49.98 - 62.44  | 5         |
| 62.45 - 74.91  | 6         |
| 74.92 - 87.30  | 5         |

This is a simplified example and the actual frequency distribution might look slightly different depending on the exact class intervals you choose.

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