1. What is Relative Frequency?

Relative Frequency is the proportion of occurrences in a dataset, calculated by dividing the frequency of an event by the total number of observations. It helps understand the distribution of data points in a dataset.

2. How Does the Calculator Work?

The calculator uses the Relative Frequency formula:

Where:

• Frequency — Number of times the event occurs (count)
• Total Observations — Total number of observations in the dataset (count)

Explanation: The result can be expressed as a decimal between 0 and 1 or as a percentage between 0% and 100% by multiplying by 100.

3. Importance of Relative Frequency

Details: Relative frequency is fundamental in statistics for understanding probability distributions, comparing datasets of different sizes, and identifying patterns in categorical data.

4. Using the Calculator

Tips: Enter the frequency count (must be ≥0) and total observations (must be >0 and ≥ frequency). The calculator will display the result as both a decimal and percentage.

5. Frequently Asked Questions (FAQ)

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

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

Q3: When should I use relative frequency?
A: When comparing categories in datasets of different sizes or when you need to standardize frequency counts.

Q4: How is relative frequency related to probability?
A: Relative frequency can serve as an empirical estimate of probability in many cases.

Q5: What if my frequency is greater than total observations?
A: This shouldn't happen - the calculator will not compute invalid inputs where frequency > total.