Do you have data that’s an anomaly or special cause that you want to exclude from your analysis? Do you want the ability to temporarily exclude certain data from your data set analysis? Special causes and outlying data can occur in any data collection process, learn how to easily handle these situations.
If you are calculating and charting average weekly temperature in a room, but find that one night the thermostat has been inadvertently set to 90 degrees, how will that data point affect your average? Clearly, the answer is that it would create a false sense of a higher temperature average for the week, and in effect create a misleading report.
There may be times that it is appropriate to leave out irregular data points such as this one, to be sure, without feeling that you’re “cheating” on the numbers. Additionally, there may be special causes that have been addressed and no longer apply to the calculations, and you’d like to remove these. Or perhaps you’d like to exclude certain pieces of data on a temporary basis, to analyze their effect on the calculations. Having the flexibility to remove or exclude anomaly data from your control chart can help you more easily focus on your process and remove any additional noise from the chart or the calculations.