About editing history data
In some cases, you may want to search through the history data and look for unusual data or “outliers.” An outlier is a data value that is far apart from the rest of the data; an extreme value that is either much lower or much higher than the rest of the values in the data set. Outliers are known to skew means or averages, so it may be helpful to identify and edit or hide this data. This doesn’t mean that the data point is necessarily bad – but in most cases the information is more helpful without the inclusion of this unusual data.
Figure 11. Configure Outliers window
- Configure Outliers check box
Outlier filtering is disabled by default. Select the check box to enable the outlier filtering feature and use the properties that are displayed in the window box. Clear the check box to disable outlier data filtering. When outlier properties are enabled, the Window size and the Percent of Std Deviation properties are available and allow you to specify the intensity of the search for outliers in the data.
- Window
Enter an integer in the
Windowproperty to define the number of surrounding data points to consider when determining whether a given point is an outlier. For example, if you use the default value of “4”, it will look at the two points before and after the point under investigation (PUI). This is a surrounding range of 4 points–from which a standard deviation will be calculated and used with the percentage properties, as described, below. - Percentage
Enter a value in this property to specify the percent of standard deviation (calculated from the window of points) to apply for identifying whether or not the PUI should be considered a valid value (not an outlier). If the PUI falls outside of this valid range, then it is considered to be an outlier and its value is replaced by the linear interpolation of the surrounding 2 valid points. If the PUI falls within the range, then the data point is used and considered valid.