Select tests for special causes for Individuals Chart

Stat > Control Charts > Variables Charts for Individuals > Individuals > I Chart Options > Tests

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.

In the drop-down list, specify whether to perform some, all, or no tests for special causes. You can make each test more or less sensitive by changing the value of K.

Tip

To change the default settings for future sessions of Minitab, choose Tools > Options > Control Charts and Quality Tools > Tests.

1 point > K 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.
K points in a row on same side of center line
Test 2 identifies shifts in the process centering. 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.
K points in a row, all increasing or all decreasing
Test 3 detects trends. This test looks for a long series of consecutive points that consistently increase in value or decrease in value.
K 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.
K out of K+1 points > 2 standard deviations from center line (same side)
Test 5 detects small shifts in the process.
K out of K+1 points > 1 standard deviation from center line (same side)
Test 6 detects small shifts in the process.
K 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.
K points in a row > 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.
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