1. What is Relative Frequency?

Relative Frequency (RF) 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:

• \( count \) — Number of times the event occurs
• \( n \) — Total number of observations

Explanation: The formula calculates what proportion of the total observations a particular event represents.

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.

4. Using the Calculator

Tips: Enter the count of the event and the total number of observations. Both values must be positive numbers, with count ≤ n.

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 observations).

Q2: Can relative frequency be greater than 1?
A: No, relative frequency always ranges between 0 and 1 (or 0% to 100% when expressed as percentage).

Q3: How is relative frequency related to probability?
A: Relative frequency can serve as an empirical estimate of probability in many cases.

Q4: What are common applications of relative frequency?
A: Used in histograms, probability distributions, survey analysis, and quality control processes.

Q5: How precise should relative frequency values be?
A: Typically reported to 2-4 decimal places depending on sample size and application requirements.