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Tab 7: Outliers
Tab 7 of the Test Distribution window displays any potential outliers in the data. These points should be reviewed to see if they are in error and replaced if this is the case. They might also represent extreme values for a long tailed distribution so transforming the data is another option. If they cannot be eliminated and a distribution cannot be fit to the data, the use of a nonparametric tolerance interval or attribute sampling plan may be required.
For each point a z-score is calculated. The z-score is:
A z-score of 10 means the value is 10 standard deviations above the average. A point is marked as likely being an outlier if it is more than 10 standard deviations from the average (z-score greater than 10 or less than -10). Robust estimates of the average and standard deviation are used for this calculation called 20% trimmed estimates. This is so that an outlier does distinguish itself by inflating the estimate of the standard deviation. Points that are from 4.5 to 10 standard deviations from the average are marked as either outliers relative to the normal distribution or extreme values from a long tailed distribution.
The outlier shown above is from a set of data generated using the largest extreme value distribution. Even though the one point is flagged as a potential outlier, it is in reality just part of a long tail as shown below.
By performing a right mouse click over the graphic or clicking the Menu button, the following popup menu will appear:
The menu items are as follows:
Size To Fit: Sizes output to fit window. Output will shrink and expand to fit window when window is resized.
Fixed Size - Normal: Sizes output so easy to read. If the output is too large to fit the window, scroll bars are added.
Fixed Size - Custom: Can specify the size of the output. If the output is too large to fit the window, scroll bars are added.
Print: Prints the output.
Copy to Clipboard: Copies the output to the clipboard in Windows Meta file (Picture) format.