You can use the Output Variables tab to add analysis variables to the data table. (See Figure 22.5.) If you request a plot that uses one of the output variables, then that variable is automatically created even if you did not explicitly select the variable on the Output Variables tab.

The following list describes each output variable and indicates how the output variable is named. represents the name of the response variable.

Predicted values

adds predicted values. The variable is named RobP_.

Final weights (M and MM methods only)

adds the final weights used in the iteratively reweighted least squares algorithm. The variable is named RobWt_.

Robust residuals

adds residuals, which are calculated as observed values minus predicted values. The variable is named RobR_.

Internally studentized robust residuals

adds internally studentized residuals, which are the residuals divided by their standard errors. The variable is named RobIntR_.

Robust MCD distance

adds a robust measure of distance between an observation and a robust estimate of location. The variable is named RobRD_.

Mahalanobis distance

adds the Mahalanobis distance between an observation and the multivariate mean of the data. The variable is named RobMD_.

Outlier indicator

adds an indicator variable for outliers. The variable is named RobOut_.

Leverage indicator

adds an indicator variable for leverage points. The variable is named RobLev_.