1. What is Relative Frequency?

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's commonly used in probability and statistics.

2. How Does the Calculator Work?

The calculator uses the Relative Frequency formula:

Where:

• \( f \) — Frequency of the specific event or value
• \( \Sigma f \) — Total frequency of all events or values
• \( RF \) — Relative Frequency (expressed as decimal)

Explanation: The formula calculates the proportion of individual frequency to the total frequency, providing a normalized measure between 0 and 1.

3. Importance of Relative Frequency

Details: Relative Frequency is essential for probability calculations, statistical analysis, data normalization, and creating frequency distributions. It allows comparison between datasets of different sizes.

4. Using the Calculator

Tips: Enter the frequency of the specific event and the total frequency of all events. Both values must be positive numbers, and individual frequency cannot exceed total frequency.

5. Frequently Asked Questions (FAQ)

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 count.

Q2: How do I convert relative frequency to percentage?
A: Multiply the relative frequency by 100 to get the percentage (RF × 100 = %).

Q3: What is the range of relative frequency values?
A: Relative frequency 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 since it represents a proportion of the total.

Q5: How is relative frequency used in probability?
A: Relative frequency can serve as an empirical estimate of probability, especially in large samples where it approximates theoretical probability.