1. What is Relative Frequency?

Relative frequency is the fraction or proportion of times a value occurs in a dataset compared to the total number of observations. It's a fundamental concept in statistics for understanding data distributions.

2. How Does the Calculator Work?

The calculator uses the relative frequency formula:

Where:

• Frequency — Number of times an event occurs
• Total — Total number of observations or trials

Explanation: The formula converts absolute counts into proportional values between 0 and 1, allowing comparison between datasets of different sizes.

3. Importance of Relative Frequency

Details: Relative frequency is essential for creating histograms, comparing datasets of different sizes, calculating probabilities, and understanding empirical distributions.

4. Using the Calculator

Tips: Enter the frequency count (must be ≥0) and total count (must be >0 and ≥ frequency). The calculator will compute the proportional value between 0 and 1.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between frequency and relative frequency?
A: Frequency is the raw count, while relative frequency is the proportion compared to the total (frequency divided by total).

Q2: How is relative frequency related to probability?
A: Relative frequency can be interpreted as empirical probability - the probability based on actual observations rather than theory.

Q3: Can relative frequency be greater than 1?
A: No, relative frequency always ranges between 0 and 1 since frequency cannot exceed the total count.

Q4: How is relative frequency used in graphs?
A: Relative frequency histograms show the proportion of data in each bin rather than counts, making different-sized datasets comparable.

Q5: What's the advantage over absolute frequency?
A: Relative frequency allows comparison between datasets of different sizes and can be interpreted as probability estimates.