Calculate relative frequency, percentage frequency, cumulative frequency, and total observations from your statistical data quickly and accurately.
Enter the frequency and total number of observations to calculate the relative frequency instantly.
| Measure | Value | Calculation |
|---|---|---|
| Frequency | — | Given frequency |
| Total Observations | — | Given total |
| Relative Frequency | — | Frequency ÷ Total |
| Percentage Frequency | — | Relative Frequency × 100 |
| Formula | f ÷ N | |
Relative frequency describes how often a particular value occurs compared with the total number of observations in a data set. Unlike ordinary frequency, which is a count, relative frequency represents a proportion of the entire data set.
Relative frequency is useful when comparing data sets of different sizes because it expresses frequencies on a common scale. It can also be converted into a percentage to make statistical results easier to understand.
Calculating relative frequency requires two values: the frequency of the specific observation and the total number of observations.
The standard formula for relative frequency is simple:
For example, if a value occurs 15 times in a data set containing 60 observations:
Suppose a teacher records the number of students who selected different study methods. If 20 students selected a particular method and there were 80 students in total, the relative frequency can be calculated as follows.
This means that the selected study method represents 25% of the observations in the data set.
Relative frequency allows observations to be compared proportionally, even when data sets contain different numbers of observations.
Relative frequencies are commonly used in statistics, probability, surveys, research, and data analysis.
Converting relative frequency to a percentage makes statistical results easier to communicate and interpret.
Relative frequency can be used when creating relative frequency histograms, bar charts, and other statistical visualizations.