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In this StatQuest episode, Josh Starmer explains ROC and AUC in a clear manner, building on concepts like confusion matrix and sensitivity/specificity. He uses an example of logistic regression with obese and not obese mice to demonstrate how ROC and AUC work, emphasizing that these concepts go beyond logistic regression. It is crucial to understand the basics before delving into the details of ROC and AUC.