Minitab provides eight tests for special causes. By default, Minitab uses only Test 1. Select additional tests based on company or industry standards. Use the tests to determine which observations to investigate, and to identify the specific patterns and trends in your data.
For more information on each of the tests and when to use them, go to Using tests for special causes in control charts.
In the drop-down list, specify whether to perform some, all, or no tests for special causes.
- One point more than 3 standard deviations from center line
- Test 1 identifies subgroups that are unusual compared to other subgroups. Test 1 is universally recognized as necessary for detecting out-of-control situations. If small shifts in the process are of interest, you can use Test 2 to supplement Test 1 in order to create a control chart that has greater sensitivity.
- Nine points in a row on same side of center line
- Test 2 identifies shifts in the process centering or variation. If small shifts in the process are of interest, you can use Test 2 to supplement Test 1 in order to create a control chart that has greater sensitivity.
- Six points in a row, all increasing or all decreasing
- Test 3 detects trends. This test looks for long series of consecutive points that consistently increase in value or decrease in value.
- Fourteen points in a row, alternating up and down
- Test 4 detects systematic variation. You want the pattern of variation in a process to be random, but a point that fails Test 4 might indicate that the pattern of variation is predictable.
- Two out of three points more than 2 standard deviations from center line (same side)
- Test 5 detects small shifts in the process.
- Four out of five points more than 1 standard deviation from center line (same side)
- Test 6 detects small shifts in the process.
- Fifteen points in a row within 1 standard deviation of center line (either side)
- Test 7 detects a pattern of variation that is sometimes mistaken as evidence of good control. This test detects control limits that are too wide. Control limits that are too wide are often caused by stratified data, which occur when a systematic source of variation is present within each subgroup.
- Eight points in a row more than 1 standard deviation from center line (either side)
- Test 8 detects a mixture pattern. In a mixture pattern, the points tend to fall away from the center line and instead fall near the control limits.