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Relative Frequency Formula:
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Relative frequency is a statistical measure that represents the proportion or percentage of times a particular value or category occurs in a dataset relative to the total number of observations. It provides a normalized way to compare frequencies across different datasets or categories.
The calculator uses the relative frequency formula:
Where:
Explanation: The relative frequency calculation converts raw frequency counts into proportional values between 0 and 1, making it easier to compare distributions across different sample sizes.
Details: Relative frequency is essential in statistics for normalizing data, comparing distributions, creating probability estimates, and building frequency distributions. It allows researchers to make meaningful comparisons between datasets of different sizes and is fundamental in probability theory and statistical analysis.
Tips: Enter the frequency count (must be ≥ 0) and total count (must be ≥ 1). The frequency cannot exceed the total value. The calculator will compute the relative frequency as a decimal value between 0 and 1.
Q1: What is the difference between frequency and relative frequency?
A: Frequency is the raw count of occurrences, while relative frequency is the proportion of occurrences 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, 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 since the frequency cannot exceed the total count.
Q4: What does a relative frequency of 0 mean?
A: A relative frequency of 0 means the event or value did not occur in the dataset.
Q5: How is relative frequency used in probability?
A: Relative frequency serves as an empirical estimate of probability - the proportion of times an event occurs in a large number of trials approximates its theoretical probability.