Statistics Tool

Histogram Maker

Create a Frequency Distribution Histogram.

Σ The Formula

Frequency = count of values in each bin | Bin Width = (Max - Min) / Number of Bins

Real World Examples

Age Distribution
Ages: 22, 25, 28, 30, 35, 40, 45 with bin size 10 → Bins: [20-30): 3, [30-40): 2, [40-50): 2
Test Scores
Scores: 65, 70, 75, 80, 85, 90, 95 with bin size 10 → Shows distribution across grade ranges
Income Ranges
Salaries: 30k, 35k, 45k, 50k, 60k, 75k with bin size 20k → Visualizes salary distribution
Measurement Data
Heights: 160, 165, 170, 175, 180 cm with bin size 5 → Shows frequency distribution

# About This Calculator

A histogram is a type of bar chart that displays the frequency distribution of continuous data by grouping values into bins (ranges). Unlike regular bar charts which show categories, histograms show how data is distributed across numerical ranges, revealing patterns like normal distributions, skewness, or outliers.

Histograms are fundamental in statistics, data analysis, quality control, and research. They're used to visualize test score distributions, analyze manufacturing tolerances, understand population demographics, examine income inequality, and identify data patterns in any field from biology to finance.

The key to good histograms is choosing appropriate bin size (width). Too few bins hide patterns; too many create noise. A common rule: use √n bins for n data points, or experiment to find what reveals your data's story best. Bins are typically [a, b) - includes a, excludes b.

This calculator automatically creates bins based on your data range and chosen bin size, counts frequencies, and generates a visual histogram. It's perfect for understanding data distribution, identifying trends, spotting outliers, or presenting statistical analysis in reports and presentations.

How To Use

  1. Enter dataset.
  2. (Optional) Set Bin Size.
  3. Click Generate.

Frequently Asked Questions

What's the difference between a histogram and a bar chart?+

Histograms show continuous numerical data grouped into ranges (bins), with no gaps between bars. Bar charts show categorical data (like countries, products) with gaps between bars. Histogram x-axis is numerical ranges; bar chart x-axis is categories.

How do I choose the right bin size?+

Start with √n bins for n data points. For 100 values, try 10 bins. Experiment: too few bins (large width) hide patterns, too many bins (small width) create noise. The goal is to reveal the data's shape - normal, skewed, bimodal, etc.

What does the shape of a histogram tell me?+

Normal (bell curve): symmetric, most data in middle. Right-skewed: tail extends right (income data). Left-skewed: tail extends left. Bimodal: two peaks (mixed populations). Uniform: flat (random data). The shape reveals underlying patterns.

Can I use this for categorical data?+

No, histograms are for continuous numerical data (heights, weights, scores). For categorical data (colors, brands, yes/no), use a bar chart or pie chart instead. The distinction is important for proper data visualization.

What are bins and how do they work?+

Bins are ranges that group data. With bin size 10 starting at 0: [0-10), [10-20), [20-30). The bracket [ means inclusive, ) means exclusive. A value of 10 goes in [10-20), not [0-10). The histogram counts how many values fall in each bin.

Is Histogram Maker free to use?+

Yes, Histogram Maker on Matheric is completely free to use. We believe in accessible education and utility for everyone.

About

A histogram is a type of bar chart that displays the frequency distribution of continuous data by grouping values into bins (ranges). Unlike regular bar charts which show categories, histograms show how data is distributed across numerical ranges, revealing patterns like normal distributions, skewness, or outliers.

Histograms are fundamental in statistics, data analysis, quality control, and research. They're used to visualize test score distributions, analyze manufacturing tolerances, understand population demographics, examine income inequality, and identify data patterns in any field from biology to finance.

The key to good histograms is choosing appropriate bin size (width). Too few bins hide patterns; too many create noise. A common rule: use √n bins for n data points, or experiment to find what reveals your data's story best. Bins are typically [a, b) - includes a, excludes b.

This calculator automatically creates bins based on your data range and chosen bin size, counts frequencies, and generates a visual histogram. It's perfect for understanding data distribution, identifying trends, spotting outliers, or presenting statistical analysis in reports and presentations.

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