AUC for someone with no stats knowledge Can someone explain what area under the curve means for someone with absolutely no stats knowledge? For example, if a model claims an AUC of 0.9, does that mean that it makes an accurate prediction 90% of the time?

To keep things reasonably simple, an AUC of 0.9 would mean that if you randomly picked one person/thing from each class of outcome (e.g., one person with the disease and one without), there is a 90% chance that the one from the class of interest (the group being modelled, here those with the disease) has the higher value (or this could be a lower value if the thing of interest was associated with the reference or default class).
So if the AUC for predicting "being male" versus "being female" using height was 0.9, this would mean that if you took a random male and a random female, 90% of the time, the male would be taller.
