The history editor view, as described in About the history editor view, provides the ability to review and modify the history data that you have collected.
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.
It is possible to alter good data and miss filtering some bad data points using the history editor view.
Workbench provides the ability to find and edit outliers based on parameters that you specify. The Configure Outliers dialog box, shown in Figure 175, appears when you click the Configure Outliers icon in the toolbar menu. Refer to About the history editor toolbar icons for a list of toolbar icons specific to the history editor view.
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Configure Outliers check box
Outlier filtering is disabled by default. Select the check box to enable the outlier filtering feature and use the parameters that are displayed in the dialog box. Clear the check box to disable outlier data filtering. When outlier parameters are enabled, the Window and the Percent of Std Deviation fields are available and allow you to specify the “intensity” of the search for outliers in the data.
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Window
Enter an integer in the Window field 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 “window” of 4 points–from which a standard deviation will be calculated and used with the percentage parameter, as described, below.
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Percentage
Enter a value in this field 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.