Laney P' Chartoverview how to example data see also
Laney P' ChartStat > Control Charts > Attributes Charts > Laney P'
The Laney P' chart is similar to a traditional P chart. Both charts help you to monitor the proportion of defective items that are produced by your process. The Laney P' chart can be useful in the following situations:
Overdispersion can cause the points on a traditional P chart to appear to be out of control when they are not. For the Laney P' chart, the definition of common cause variation includes not only the within-subgroup variation, but also the average variation between consecutive subgroups. If there is overdispersion, the control limits on a Laney P' chart are wider than those of a traditional P chart. The wider control limits mean that only important deviations in your process are identified as out of control.
Underdispersion, which can occur with subgroups of any size, is often caused by a lack of randomness. Underdispersion can result in control limits that are too wide for the data. The Laney P' chart corrects for underdispersion by calculating narrower control limits.
You can use the P Chart Diagnostic to test for overdispersion and underdispersion.
The calculations for the Laney P' chart include Sigma Z, which is an adjustment for overdispersion or underdispersion. A Sigma Z value of 1 indicates that no adjustment is necessary and that the Laney P' chart is exactly the same as a traditional P chart.
See [8] for more discussion about Laney P' charts.
Variables: Enter the columns that contain the number of defectives for each subgroup.
Subgroup sizes: Enter a number or a column that contains the subgroup sizes. If the subgroups are not equal, each control limit is not a single straight line but varies with the subgroup size. If the subgroup sizes do not vary much, you can set a constant subgroup size so that the control limits remain constant. To set a constant subgroup size for your chart, use P' Chart Options > Limits.