Class Width Calculator

Calculate optimal class width for histograms and frequency distributions

Calculate Class Width

Highest value in your dataset

Lowest value in your dataset

Desired number of intervals

Class Width Results

Range
0.00
Max - Min = 0 - 0
Class Width (Exact)
0.0000
Range ÷ Number of Classes
Class Width (Rounded)
0
Rounded up for practical use
Formula Used
Class Width = (Max - Min) ÷ n
Where n = number of classes

Class Width Analysis

Example: Student Test Scores

Test Score Data

Scores: 45, 68, 82, 79, 67, 55, 75, 55, 85, 89, 90, 78, 45, 66, 49

Maximum score: 90

Minimum score: 45

Desired classes: 9

Calculation Steps

1. Range = 90 - 45 = 45

2. Class Width = 45 ÷ 9 = 5

3. Final Class Width = 5

4. Classes: 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, 85-89

Class Width Guidelines

1

Choose Classes

5-20 classes work best

Too few = oversimplified, too many = cluttered

2

Calculate Width

Width = Range ÷ Classes

Round up to convenient numbers

3

Create Intervals

Use equal-width intervals

Ensure no gaps or overlaps

Quick Tips

Round class width to convenient numbers (5, 10, 25, etc.)

All class intervals should have the same width

Choose class boundaries that don't split data points

Consider your audience and the purpose of the histogram

Understanding Class Width in Statistics

What is Class Width?

Class width is the difference between the upper and lower boundaries of any class interval in a frequency distribution. It represents the range of values that each class covers and is essential for creating meaningful histograms and frequency distributions.

Why is Class Width Important?

  • Creates clear visual representation of data distribution
  • Helps identify patterns and trends in datasets
  • Essential for creating accurate histograms
  • Facilitates data analysis and interpretation

Formula and Calculation

Class Width = (Maximum - Minimum) ÷ Number of Classes

  • Maximum: Highest value in the dataset
  • Minimum: Lowest value in the dataset
  • Range: Maximum - Minimum
  • Number of Classes: Desired number of intervals

Tip: Round the calculated class width up to the nearest convenient number for easier interpretation and plotting.

Choosing the Right Number of Classes

Too Few Classes (<5)

Oversimplifies data, loses important details, may miss distribution patterns

Optimal Range (5-20)

Balances detail with clarity, reveals distribution shape, easy to interpret

Too Many Classes (>20)

Creates clutter, may hide patterns, difficult to interpret visually