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 probability distributions.

2. How Does the Calculator Work?

The calculator uses the relative frequency formula:

Where:

• \( f \) — Frequency of the specific event or category
• \( total \) — Total number of observations or trials

Explanation: The formula divides the count of a specific outcome by the total count of all possible outcomes, giving a proportion between 0 and 1.

3. Importance of Relative Frequency

Details: Relative frequency is essential for probability estimation, statistical analysis, and data visualization. It allows comparison between datasets of different sizes and forms the basis for empirical probability.

4. Using the Calculator

Tips: Enter the frequency count of your specific event and the total count of all events. Both values must be positive numbers, with total > 0.

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 (frequency divided by total count).

Q2: What are possible values for relative frequency?
A: It ranges from 0 (never occurs) to 1 (always occurs), often expressed as a percentage (0% to 100%).

Q3: How is relative frequency related to probability?
A: Relative frequency from empirical data approximates theoretical probability as sample size increases.

Q4: Can relative frequency be greater than 1?
A: No, since frequency can't exceed the total count, relative frequency is always ≤1.

Q5: How is relative frequency used in histograms?
A: Histograms can display relative frequencies on the y-axis to show proportion rather than raw counts.