The relative frequency calculator is a user-friendly tool used in statistics that determines the frequency or probability of a specific event or outcome occurring within a larger data set.
Relative Frequency In Statistics:
“A relative frequency is a type of frequency that is defined as how many times a specific kind of data or event occurs within the total number of observations”.
In simple words, relative frequency is how often something happens divided by all outcomes. It is always in a percentile form.
Relative Frequency Expressions:
The relative frequency formula is:
RF = f / n
- RF = Relative Frequency
- n = Total number of frequencies
- f = How many times the data occurred in a single observation
Calculations and Examples:
If you have any confusion about how to calculate relative frequency, we have an example through which you can learn how to calculate manually.
Let’s assume your team played 10 football matches and won 7 of them now calculate its relative frequency.
The frequency of winning = 7
The Total Frequencies = 10
The relative frequency = 7/10
The relative frequency = 0.70
Now multiply it by 100 to convert it into percentile form.
The relative frequency = 0.70 x 100
The relative frequency = 70%
Steps to Use Relative Frequency Calculator:
By using this calculator, you can get quick and accurate results by simply entering a couple of inputs such as:
What to do:
- Enter the data set values for relative frequency, separated with commas (,)
- Select the Individuals or Group frequencies accordingly
- Press the Calculate button
What you get:
- Relative frequencies in a table form
- Other statistical characteristics
- Graph of given data set
What is relative vs. normal frequency?
In frequency analysis, a value or category is counted as many times as it appears in a dataset, whereas finding relative frequency is the percentage or proportion of that value or category in the dataset.
Why is it important to use relative frequency?
According to the Relative Frequency, a score occurs a certain proportion of the time. Because it is based on likelihood, it is more straightforward to interpret than a straightforward frequency calculation.
Statisticsbyjim.com: Relative Frequencies and Their Distributions, Frequencies vs. Relative Frequencies, How to Find a Relative Frequency and Cumulative Relative Frequency Distributions