Cumulative relative frequency graph
Cumulative relative frequency graph

This article "Cumulative relative frequency graph" explains about what is relative frequency and cumulative frequency?٫ what is a cumulative frequency and How to calculate cumulative frequency percentage.


What is the cumulative relative frequency graph?

Cumulative relative frequency (CRF) is an important metric in data analysis. It can be used to estimate the occurrence of certain events or events that have occurred repeatedly within a given sample, such as a hospital population. 

In simple terms, it is the percentage of times that something occurs at its target value divided by the total number of occurrences. For example, the % of time someone visits the website would be calculated first, then the age for those visits, and so forth. Then we could compare the average age and age per visit to get the overall average in our sample. However, this method can be quite difficult to interpret if things are not grouped in order of occurrence.

A “” cumulative total” is calculated by summing up all occurrences from the first event and subtracting the second event. Therefore, it becomes easier to see if there are any differences between the previous two cases. If there are no major differences, the result will be zero so that it is possible to compare both examples. Conversely, if there are significant differences between the two instances, the sum will rise above 0 and indicate there are more than one instance of some type of interaction or interaction. Therefore, it is easy to make decisions about which set of interactions is most frequent. For example, the “” %” would be much larger where there are more occurring events or activities.


Cumulative relative frequency graph is a plot used when looking at the histogram of values for some given dataset or in case of time series analysis. It measures the mean number of times in which these values occur in your data.


A cumulative relative frequency graph of a quantitative variable is a curve graphically showing the cumulative relative frequency distribution.


So knowing about the cumulative relative frequency graph, is important for finding patterns with the data and analyzing any changes with time. In that sense, it helps us when we want to analyze big datasets in order to understand why there are certain events happening. This graph shows the trends over time of both individual instances and aggregates of items in your dataset.


How do I find my cumulative frequency graph?


Example: Aslam is a farmer who grows his own onions. Each onion costs him 7 p to grow. He measures the weight of 80 onions he has grown. The cumulative frequency graph summarises his results.


Aslam sells all 80  onions using the price list below.

Cumulative frequency graph
Cumulative frequency graph

Cumulative frequency graph
Cumulative frequency graph

Cumulative relative frequency graph

Cumulative relative frequency graph
Cumulative relative frequency graph