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Calculating Relative Frequency Statistics

Relative Frequency Formula:

\[ RF = \frac{f}{n} \]

Where:

  • \( RF \) = Relative Frequency (decimal)
  • \( f \) = Frequency of Class (count)
  • \( n \) = Total Sample (count)

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1. What is Relative Frequency?

Relative frequency is a statistical measure that shows the proportion or percentage of times a particular value occurs in a dataset relative to the total number of observations. It is commonly used in histograms, frequency tables, and statistical analysis.

2. How Does the Calculator Work?

The calculator uses the relative frequency formula:

\[ RF = \frac{f}{n} \]

Where:

Explanation: The formula calculates what fraction of the total observations belong to a particular class or category.

3. Importance of Relative Frequency

Details: Relative frequency is essential for comparing distributions across different sample sizes, creating probability estimates, and understanding the proportional composition of datasets in statistical analysis.

4. Using the Calculator

Tips: Enter the frequency count for the specific class and the total sample size. Ensure frequency is not greater than total sample, and both values are positive numbers.

5. Frequently Asked Questions (FAQ)

Q1: What's 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 sample size.

Q2: How do I convert relative frequency to percentage?
A: Multiply the relative frequency by 100. For example, RF = 0.25 equals 25%.

Q3: Can relative frequency be greater than 1?
A: No, relative frequency ranges from 0 to 1, where 0 means no occurrences and 1 means all observations belong to that class.

Q4: When should I use relative frequency instead of absolute frequency?
A: Use relative frequency when comparing datasets of different sizes or when you need proportional information for probability calculations.

Q5: How is relative frequency used in histograms?
A: In relative frequency histograms, the vertical axis shows proportions rather than counts, making it easier to compare distributions with different sample sizes.

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