Relative Frequency Formula:
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Relative frequency 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 the ratio of specific occurrences to total occurrences, providing a standardized measure between 0 and 1 (or 0% to 100% when multiplied by 100).
Details: Relative frequency is essential for understanding probability distributions, analyzing categorical data, comparing datasets of different sizes, and making statistical inferences about populations.
Tips: Enter the observed frequency (count of specific occurrences) and total frequency (overall count of all observations). Both values must be positive numbers, and observed frequency cannot exceed total frequency.
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 occurrences relative to the total (frequency divided by total).
Q2: How do I convert relative frequency to percentage?
A: Multiply the relative frequency by 100. For example, a relative frequency of 0.25 equals 25%.
Q3: Can relative frequency be greater than 1?
A: No, relative frequency always ranges from 0 to 1 (or 0% to 100%) since observed frequency cannot exceed total frequency.
Q4: When is relative frequency used in statistics?
A: It's used in probability calculations, creating histograms, analyzing survey data, quality control, and comparing distributions across different sample sizes.
Q5: What does a relative frequency of 0.5 mean?
A: A relative frequency of 0.5 means that the event occurs in 50% of the observations, or half the time in the dataset.