Data considerations for I-MR Chart

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

The data should be continuous

If your data are counts of defectives or defects, use an attribute control chart, such as P Chart or U Chart.

The data should be in time order

Because control charts detect changes over time, the order of the data is important. You should enter the data in the order it was collected, with the oldest data at the top of the worksheet.

The data should be collected at appropriate time intervals

Collect data at equally spaced time intervals, such as every hour, every shift, or every day. Select a time interval that is short enough that you can identify changes to the process soon after the changes occur.

The data should be individual observations that are not collected in subgroups

If you can collect data in subgroups, use Xbar-R Chart or Xbar-S Chart.

The data should include at least 100 total observations

If you have fewer than the recommended number of observations, then you can still use the control chart, but the results are preliminary because the control limits may not be precise. If you use the chart regularly, re-estimate the standard deviation and the control limits after you collect the recommended number of observations.

The data should be moderately normal

If the data are very skewed, you could try a Box-Cox transformation to see if that corrects the nonnormal condition. If your process naturally produces nonnormal data and the transformation is effective, you can use the chart of the transformed data to assess the stability of your process.

The observations should not be correlated with each other

If consecutive data points are correlated, the control limits will be too narrow and you may see a large number of false out-of-control signals.