The Quantile Range Outliers method of outlier detection uses the quantile distribution of the values in a column to locate the extreme values. Quantiles are useful for detecting outliers because there is no distributional assumption associated with them. Data are simply sorted from smallest to largest. For example, the 20th quantile is the value at which 20% of values are smaller. Extreme values are found using a multiplier of the interquantile range, the distance between two specified quantiles. For more details about how quantiles are computed, see Quantiles in the Basic Analysis book.

The Quantile Range Outliers panel enables you to specify how outliers are to be calculated and how you want to manage them. Figure 2.6 shows the default Quantile Range Outliers window.

Figure 2.6 Quantile Range Outliers Window

An outlier is considered any value more than Q times the interquantile range from the lower and upper quantiles. You can adjust the value of Q and the size of the interquantile range.

The multiplier that helps determine values as outliers. Outliers are considered Q times the interquantile range past the Tail Quantile and 1 - Tail Quantile values. Large values of Q provide a more conservative set of outliers than small values. The default is 3.

Turns on the exclude row state for outliers in the selected columns in the Quantile Range Outliers Report. Click Rescan to update the Quantile Range Outliers report.

Adds the selected outliers to the missing value codes column property. Use this option to identify known missing value or error codes within the data. Missing value and error codes are often integers and are sometimes either a positive or negative series of nines. Click Rescan to update the Quantile Range Outliers report.

Changes the outlier value to a missing value in the data table. Use caution when changing values to missing. Change values to missing only if the data are known to be invalid or inaccurate. Click Rescan to update the Quantile Range Outliers report.

Adds the selected outlier values to the missing value codes column property. You must click Rescan to update the Quantile Range Outliers report.

Note: The first time you use choose an action (such as Change to Missing or Exclude Rows) to change your data, the alert window warns you to use the Save As command to save your data table as a new file to preserve a copy of your original data. When this window appears, click OK. If you decide to save your new data file, you will automatically be prompted to save the file with a new name.