This index, denoted A(z) to symbolize its Gaussian underpinnings, varies from 0.5 (no apparent accuracy)
to 1.0 (perfect accuracy) as the ROC curve moves towards the left and top boundaries of the ROC graph^2
When one fits the two parameters by maximum likelihood rather than by eye, one also obtains their standard errors,
thereby allowing the area derived from the two parameters to be also accompanied by a standard error. This can be
used to construct confidence intervals and to perform statistical tests of significance.