To determine the frequency density in a histogram, you divide the frequency by the class width for each interval.

In a histogram, frequency density plays a crucial role in accurately representing data when class widths vary. This approach ensures that the area of each bar corresponds to the frequency of data within that interval. To compute the frequency density, two key pieces of information are required: the frequency (which is the count of data points within a specific class interval) and the class width (which is the range of values encompassed by that interval).

First, identify the frequency for each class interval. This information is typically provided in a frequency table or can be calculated directly from the data set. Next, ascertain the class width for each interval by subtracting the lower boundary from the upper boundary. For example, if a class interval spans from $10$ to $20$, the class width can be calculated as:

After determining both the frequency and the class width, you can calculate the frequency density by using the formula:

For instance, if the frequency is $30$ and the class width is $10$, the frequency density would be:

This indicates that the height of the bar in the histogram for that particular interval should be $3$.

By utilizing frequency density, histograms can effectively represent data, even when class intervals differ in width. This method enhances the ability to compare the distribution of data across various intervals, providing a clearer understanding of the data’s overall pattern.