If the relative frequency is the result of dividing the Absolute frecuency of a certain value between the total number of recorded data, the relative absolute frequency will be the number resulting from dividing the accumulated frequency by the total number of records. This concept is extremely important in understanding the accounting, since it helps us to identify numerical trends: the figure whose frequency is closest to unity will be the one with the greatest probability of leaving.

## How is the relative absolute frequency calculated?

Taking into account that the absolute frequency gives us very valuable information about the number of times an event is repeated when performing a specific number of random experiments, the relative frequency is translated as the division of the absolute frequency of some determined value in the population between the total of values that make up said population. Therefore, if we want to find the relative absolute frequency, we will inevitably have to calculate the absolute frequency.

Thus, taking into account that the relative frequency is represented by the formula*hi*, the absolute frequency with the letters *fi*and the total of values that make up the population or the sample with the letter N:

hi = fi / N

When doing these calculations we will see that the relative absolute frequency will be bounded between the numbers 0 and 1 (since the frequency of the sample values will always be less than the total size of the sample itself) and that the sum of all the frequencies Relative values will be 100 when measured in percent.

## Differences between relative absolute frequency and cumulative absolute frequency

Given that the accumulated absolute frequency is the sum of the absolute frequencies of all the values equal to or less than the studied value, the accumulated relative frequency will be the result of dividing the accumulated frequency by the total number of data in the study.