Summary

Provides a graphical means for looking at data dynamically (over time). Run charts often show patterns that do not appear in static displays of your data, such as histograms. The run chart is a useful tool for discovering evidence of influences on the process, all of which can be used to make process improvements

Answers the question:
  • Does the process exhibit any patterns (for example, trends, cycles, sawtooth, and mixtures) over time?
When to Use Purpose
Start of project While performing a baseline analysis, you typically use a control chart to verify that the process was stable. The run chart is an additional tool that tests for patterns that may not be detected in a control chart, yet may often reveal clues for making process improvements.
Mid-project The first rule of data analysis is to graph the data before running statistical tests. Whenever you collect data over time, you should also graph the data over time to examine its dynamic behavior. The run chart provides tests for trends, cycles, and other patterns.

Data

Numeric data (continuous or discrete) collected over time

How-To

You can use one of three ways to enter the data in Minitab:

  1. With no subgroups, enter the data into a single column.
  2. With subgroups, enter the Y data into a single column and the subgroup indicators in another column. If the subgroups are all the same size you can use a constant in lieu of the second column.
  3. With subgroups, enter the data into multiple columns in the worksheet, where each row is a subgroup.

Guidelines

The tests that appear in the run chart provide various insights into the process behavior over time.

  • If the mixtures test is significant (small p-value), then you are most likely collecting data from different sources, which could be different suppliers, different machines, and so on. However, basically, there is a consistent difference between subgroups causing the behavior you see.
  • If the cluster test is significant, then the process appears to be shifting at various points in time.
  • Oscillation may be a result of tool wear or other causes.
  • Trends are also caused by an outside influence.
By using this site you agree to the use of cookies for analytics and personalized content.  Read our policy