SUPPORT

Support Resolution Time Histogram

A histogram groups continuous numeric observations into adjacent ranges and counts how many observations fall in each range. This example uses customer-support ticket resolution time, with two-hour bins from zero to twelve hours. The bar heights show where resolution times cluster and whether a smaller group of tickets takes much longer. This is different from a bar chart of issue categories: the order of histogram bins comes from the numeric scale, and the bars touch because the ranges are continuous. Start with raw values or a clear frequency table, choose sensible equal-width bins, and label both the measure and the count. Adjust the bin width if the chart hides useful structure or becomes too noisy.

UPDATED 2026-09-25
TYPEBar
EXAMPLESupport Resolution Time Histogram
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CASE ANALYSIS

Scenario

Understanding ticket-resolution times

Key decisions

  • Metric: Measure from ticket creation to resolution.
  • Bins: Group continuous time values into equal ranges.
  • Service level: Compare the distribution with the stated response target.

When to reuse this

Use this histogram to explain a numeric distribution before choosing a service-level improvement focus.

FAQ

Frequently asked questions

What data do I need for a histogram?01
You need numeric observations, such as times, scores, sizes, or measurements, or a frequency table for numeric ranges.
What is a bin?02
A bin is one numeric interval used to group observations, such as 2–4 hours.
Can I choose the bin width?03
Yes. Choose a width that shows the distribution clearly and use equal widths unless there is a reason not to.
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