Modeling and Multivariate Methods - SAS

452 Correlations and Multivariate Techniques Chapter 17
Multivariate Platform Options
Figure 17.4 Example of an Outlier
Mahalanobis Distance
The Mahalanobis Outlier Distance plot shows the Mahalanobis distance of each point from the multivariate
mean (centroid). The standard Mahalanobis distance depends on estimates of the mean, standard deviation,
and correlation for the data. The distance is plotted for each observation number. Extreme multivariate
outliers can be identified by highlighting the points with the largest distance values. See “Computations and
Statistical Details” on page 454, for more information.
Jackknife Distances
The Jackknife Distances plot shows distances that are calculated using a jackknife technique. The distance
for each observation is calculated with estimates of the mean, standard deviation, and correlation matrix
that do not include the observation itself. The jack-knifed distances are useful when there is an outlier. In
this case, the Mahalanobis distance is distorted and tends to disguise the outlier or make other points look
more outlying than they are.
T 2 Statistic
The T 2 plot shows distances that are the square of the Mahalanobis distance. This plot is preferred for
multivariate control charts. The plot includes the value of the calculated T 2 statistic, as well as its upper
control limit. Values that fall outside this limit might be outliers.
Saving Distances and Values
You can save any of the distances to the data table by selecting the Save option from the red triangle menu
for the plot.
Note: There is no formula saved with the distance column. This means that the distance is not recomputed
if you modify the data table. If you add or delete columns, or change values in the data table, you should
select Analyze > Multivariate Methods > Multivariate again to compute new distances.