Relative Frequency Formula:
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Relative Frequency (RF) is a statistical measure that represents the proportion or percentage of times a particular value occurs in a dataset relative to the total number of observations. It provides insight into the distribution and probability of events.
The calculator uses the Relative Frequency formula:
Where:
Explanation: The formula calculates what fraction of the total observations is represented by a particular frequency, providing a normalized measure for comparison.
Details: Relative frequency is essential in statistics for understanding probability distributions, analyzing categorical data, making predictions, and comparing datasets of different sizes. It forms the basis for empirical probability calculations.
Tips: Enter the frequency (count of specific events) and total frequency (sum of all events). Both values must be positive numbers, and frequency cannot exceed total frequency. The result is displayed as a proportion between 0 and 1.
Q1: What is the difference between frequency and relative frequency?
A: Frequency is the actual count of occurrences, while relative frequency is the proportion of that count relative to the total number of observations.
Q2: How do I convert relative frequency to percentage?
A: Multiply the relative frequency by 100. For example, RF = 0.25 equals 25%.
Q3: What is the range of relative frequency values?
A: Relative frequency always ranges from 0 to 1, where 0 means the event never occurs and 1 means it always occurs.
Q4: Can relative frequency be greater than 1?
A: No, relative frequency cannot exceed 1 because frequency cannot be larger than total frequency.
Q5: How is relative frequency used in probability?
A: Relative frequency serves as an estimate of probability in empirical probability calculations, especially when theoretical probability is unknown.