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Diagram · CC BY 4.0

Bimodal histogram example

Two separate peaks from a mixture of two normal distributions, 40% and 60%.

Histogram with a bimodal shape (two peaks). The bars are the expected counts for 1,000 observations from a mixture of two normal distributions: 40% from a normal with mean 0 and standard deviation 1, and 60% from a normal with mean 4.5 and standard deviation 0.8. The bins have width 0.5 and run from −3 to 7. The dashed curve is the mixture density scaled to the same counts (1,000 × 0.5 × density). A key below the chart names the bars and the curve.

Swipe sideways to see the whole diagram, or download the PNG.

Histogram shape - bimodal. Derek Jansen, Grad Coach, CC BY 4.0.

What it shows

A histogram with two peaks. A shape like this can indicate that two groups have been measured together, such as two cohorts or two machines.

The bars are the expected counts for 1,000 observations from a mixture: 40% from one normal distribution and 60% from another. The right-hand peak is taller because more observations come from it, and narrower because its spread is smaller.

How to read it

  1. The left peak reaches 77, around zero.

  2. The right peak reaches 140, around 4.5.

  3. The dip between them, down to 10, separates two groups rather than one wide one.

The numbers behind it

  • 40% from a normal distribution with mean 0 and standard deviation 1; 60% from a normal distribution with mean 4.5 and standard deviation 0.8.
  • n = 1,000, bins of width 0.5 from −3 to 7.
  • Counts, left to right: 2, 7, 18, 37, 60, 77, 77, 60, 37, 18, 10, 16, 46, 96, 140, 140, 96, 45, 15, 3.
  • 0.11% of the distribution lies outside the plotted range.

Ways to use it in teaching

  • Have students estimate where the mean falls, then note how few observations lie near it.

  • It leads naturally into the idea of a hidden grouping variable, ahead of stratified analysis.

  • Compare it with the multimodal histogram and discuss how many groups each suggests.

For how charts like this one are chosen and reported in a results chapter, see our guide to analyzing quantitative results.

Sources

Standard formulas for the normal, gamma and uniform distributions.

Statistics

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