add pdfs

exercises/evaluation-tex/ex_rnw/ex_roc-curve_2.Rnw

@@ -49,17 +49,18 @@ Watch as the instructor demonstrates how to plot the ROC curve using $\hat{\pi}_
 \begin{itemize} 
 \item Complete the ROC curve for $\hat{\pi}_1$. 
 \item Plot the ROC curves for $\hat{\pi}_2$, $\hat{\pi}_3$, and $\hat{\pi}_4$.
-\item Manually calculate the AUC for each classifier and the average predicted probability for each classifier across all 7 observations and compare the results. 
+\item Manually calculate the AUC for each classifier and compare the results. 
+\item Compute the prevalence and the average of the predicted probability of each classifier across all 7 observations.
 \end{itemize}
 
 \item Step 3: Within your group, discuss:
 \begin{itemize} 
 \item How the differences in predictions affect the ROC curves and AUC values. 
-\item What can you say about the average predicted probability for each classifier? Compare this with the prevalence.
-\item For group A students: Assume you want to obtain a high partial AUC for low FPR values (e.g., FPR $< 0.2$). What can you say about the partial AUC of the four classifiers?
+\item The differences between average predicted probability and the prevalence. 
+\item Group A students: Assume you want to obtain a high partial AUC (pAUC) for low FPR values (e.g., using the constraint: FPR $< 0.2$). Compare the pAUC of the four classifiers.
 \item Key takeaways from comparing the four classifiers. 
 \end{itemize}
 
-\item Step 4: Formulate 1-2 challenging TRUE-FALSE questions about ROC curves. Nominate a group leader to present one question to the class and explain its relevance. 
+\item Step 4: Formulate 1-2 challenging TRUE-FALSE questions about ROC curves and post them into the Etherpad in Moodle. Nominate a group leader to present one question to the class and explain its relevance. 
 \end{itemize}