How to Determine Histogram Bin Intervals
To show a useful spread of data, you may need to estimate the ideal histogram bin interval. Here's how:
- Count the number of data points.
- Take the square root of the number of data points and round up to determine the number of bins required.
- Divide the specification tolerance (USL-LSL or Max-Min value) by number of bins.
For example:
- 25 data points = 5 bars
- 100 data points = 10 bars
If there are too many bars (e.g., more than 50) to display nicely on the page, we limit the number of bars.
Juran's Quality Control Handbook provides these guidelines for the number of bars and states that they are not "rigid" and should be adjusted when necessary.
| Number of Data Points | Number of Bars |
20-50 |
6 |
| 51-100 | 7 |
| 101-200 | 8 |
| 201-500 | 9 |
| 501-1000 | 10 |
| 1000+ | 11-20 |
Learn More
- Watch video of how to create a histogram using the QI Macros
- Histogram Examples
- Histogram in Excel
- Make a Histogram in Excel
- Comparing Histograms
- Process Capability Analysis with Cp, Cpk, Pp, Ppk
- Frequency Histogram
- Frequency Histogram Examples
