Frequency Polygon Calculator

Create frequency polygons and ogive graphs from your data with statistical analysis

Create Frequency Polygon

Enter up to 50 values separated by commas

Example: Student Test Scores

Sample Data

Test Scores: 85, 92, 78, 85, 90, 87, 85, 93, 89, 85, 88, 91, 86, 84, 87

Expected Results

• Most frequent score: 85 (appears 4 times)

• Score range: 78 to 93 points

• Frequency polygon will show distribution pattern

• Ogive graph will show cumulative frequency progression

Key Features

📈

Frequency Polygon

Line graph connecting frequency points

📊

Ogive Graph

Cumulative frequency distribution

🔢

Statistics

Mean, median, mode, and more

📋

Frequency Table

Detailed distribution breakdown

Usage Tips

Enter up to 50 numerical values separated by commas

Choose grouped data for large datasets with many unique values

Use ungrouped data for smaller datasets with distinct values

Toggle between frequency polygon and ogive graph views

Understanding Frequency Polygons

What is a Frequency Polygon?

A frequency polygon is a line graph that displays the frequency distribution of a dataset. It's created by plotting points representing the frequency of each value or class interval and connecting these points with straight lines.

Key Characteristics

  • Shows distribution shape and patterns
  • Easy to compare multiple distributions
  • Highlights peaks (modes) and trends
  • Alternative to histograms for continuous data

Ogive Graph (Cumulative Frequency)

An ogive is a cumulative frequency polygon that shows how frequencies accumulate. Each point represents the total number of observations up to that value.

Applications

  • Quality control in manufacturing
  • Educational assessment analysis
  • Market research and surveys
  • Scientific data visualization

Frequency Polygon vs Histogram

Frequency Polygon:
  • • Line graph connecting points
  • • Shows continuous flow of data
  • • Better for comparing distributions
  • • Emphasizes trends and patterns
Histogram:
  • • Bar chart with adjacent rectangles
  • • Shows discrete intervals
  • • Better for showing exact frequencies
  • • Emphasizes individual class frequencies