Relative Frequency Histogram
What it is
A relative frequency histogram looks exactly like a normal histogram, but the bar heights show the proportion of the data in each bin instead of the raw count. Each bar is the count for that bin divided by the total number of values, usually shown as a percent. All the bars add up to 100 percent.
Why use proportions
Two reasons. First, proportions let you compare datasets of different sizes on the same scale: a class of 20 and a class of 200 both add up to 100 percent, so their shapes line up. Second, relative frequency is the bridge to probability, since the proportion in a bin estimates the chance a new value lands there.
How to compute it
- Build the frequency table as usual, counting values per bin.
- Divide each count by the total number of values.
- Multiply by 100 for a percent.
That is the only change from a plain histogram. The counts become fractions of the whole.
Make one instantly
In the histogram maker, set the Show option to "Relative frequency" and the y-axis switches from counts to percentages. The frequency distribution table already lists the relative frequency column for every class, so you can read the exact numbers next to the chart.
Frequently asked questions
- What is a relative frequency histogram?
- A histogram where each bar shows the proportion of data in that bin (count divided by total, as a percent) instead of the raw count. The bars add up to 100 percent.
- How is it different from a regular histogram?
- The shape is identical. Only the y-axis changes, from counts to proportions. That lets you compare datasets of different sizes on the same scale.
- How do I calculate relative frequency?
- Divide the frequency of each bin by the total number of values, then multiply by 100 to get a percent. The tool on this site does it for you.