Enter the dataset values, choose the frequency, and click on the “Calculate” button to get the relative frequency table & graph.
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Use this relative frequency calculator statistics to find how many times a particular value occurs within the given dataset relative to the total number of observations. Our calculator generates a relative frequency distribution table for grouped or ungrouped data, showing intervals, frequencies, relative frequencies, and cumulative frequencies to help you understand data distribution.
The relative frequency is the ratio of the number of times an event occurs to the total number of trials. This frequency can be represented as a fraction, percentage, or decimal value.
Relative Frequency = f n
Where:
Cumulative relative frequency is the accumulation of previous relative frequencies. To get this, add all previous relative frequencies to the current relative frequency. The last value becomes 1, representing 100% of the data. It helps to understand the proportion of the data that falls below a specific value.
Suppose 100 students of a class got the grades A, B, C, D, and F:
Find the relative and cumulative frequency
Solution:
Calculate the relative frequency for each grade:
Calculate the cumulative relative frequency:
A = 0.2
B = 0.2 + 0.2 = 0.4
C = 0.2 + 0.2 + 0.2 = 0.6
D = 0.2 + 0.2 + 0.2 + 0.2 = 0.8
F = 0.2 + 0.2 + 0.2 + 0.2 + 0.2 = 1.0
Result Interpretation:
The following relative frequency table shows the experimental probabilities for the given data.
Numbers |
Frequency |
Relative Frequency |
Cumulative Relative Frequency |
10 |
1 |
0.2 |
0.2 |
20 |
1 |
0.2 |
0.4 |
30 |
1 |
0.2 |
0.6 |
25 |
1 |
0.2 |
0.8 |
15 |
1 |
0.2 |
1 |
You can simplify your data analysis by using our relative frequency distribution calculator and generate similar results for your dataset in seconds!
Both of these terms are closely related to each other but they are not the same.
Relative frequency is a crucial factor when you need to compare datasets of different sizes. With the help of it, you can convert the counts to proportions and compare value distribution for different groups of data. Meanwhile, the distribution of values is necessary for data analysis.
Using the cumulative relative frequency calculator, you can efficiently determine relative frequencies and gain valuable insights into your data.
Reference:
From the source of Wikipedia: Frequency, Relative Frequency.
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