When creating a frequency table, the first thing you must determine is the data set you are working with. Specifically, you need to identify the following:

1. Categories or Intervals: Decide if your data needs to be grouped into categories (for categorical data) or intervals (for continuous data). For continuous data, this might involve defining class intervals (ranges).

2. Range: For numerical data, determine the range of the data, which is the difference between the maximum and minimum values. This helps in deciding how to group data or set intervals.

3. Frequency Count: Count how often each category or interval occurs within the data set.

4. Cumulative Frequency (optional): If needed, calculate cumulative frequencies, which show how data accumulates up to a certain point.

5. Relative Frequency (optional): You may also calculate the relative frequency, which shows the proportion of each category or interval in comparison to the whole data set.

Would you like more detailed examples or have any further questions on this?

Here are five related questions:

1. What is the difference between absolute and relative frequency in a table?
2. How do you decide on the number of intervals or bins for continuous data?
3. What is the purpose of cumulative frequency in a frequency table?
4. How can a frequency table be used to create a histogram?
5. What are the common mistakes made when creating frequency tables?

Tip: Always ensure the intervals in a frequency table do not overlap, and make sure they cover the entire range of the data set.