In statistics, the frequency or absolute frequency of an event ${\displaystyle i}$ is the number ${\displaystyle n_{i}}$ of times the observation has occurred/been recorded in an experiment or study. These frequencies are often depicted graphically or tabular form.

The cumulative frequency is the total of the absolute frequencies of all events at or below a certain point in an ordered list of events.

The relative frequency (or empirical probability) of an event is the absolute frequency normalized by the total number of events:

The values of ${\displaystyle f_{i}}$ for all events ${\displaystyle i}$ can be plotted to produce a frequency distribution.

In the case when ${\displaystyle n_{i}=0}$ for certain ${\displaystyle i}$, pseudocounts can be added.

A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc. Some of the graphs that can be used with frequency distributions are histograms, line charts, bar charts and pie charts. Frequency distributions are used for both qualitative and quantitative data.

Generally the class interval or class width is the same for all classes. The classes all taken together must cover at least the distance from the lowest value (minimum) in the data to the highest (maximum) value. Equal class intervals are preferred in frequency distribution, while unequal class intervals (for example logarithmic intervals) may be necessary in certain situations to produce a good spread of observations between the classes and avoid a large number of empty, or almost empty classes.

The following are some commonly used methods of depicting frequency: