diff --git a/README.md b/README.md
index ffa4bfb..5ae1a92 100644
--- a/README.md
+++ b/README.md
@@ -160,7 +160,14 @@ with different number of samples. The program takes no arguments and prints
 a table of the result and its error for each method.
 To visualise the results, you can plot the table by doing:
 
-    $ ex-5/main | ex-5/plot.py
+    $ ex-5/bin/main | ex-5/plot.py
+
+(optional) `ex-6/plots/fit.py` makes the plot (shown in exercises.pdf, fig. 13)
+of the standard deviation vs function calls for the plain MC method. The
+program takes the tabular results of `ex-5/bin/main` as input, so run it as:
+
+
+    $ ex-5/bin/main | ex-5/plot.py
 
 
 ### Exercise 6
@@ -227,3 +234,6 @@ To plot the result of the linear classification pipe the output to
 newly generated datasets (`-i` to set the number of test iterations). The
 program prints the statistics of the number of false positives, false
 negatives and finally the purity and efficiency of the classification.
+
+(optional) `ex-7/plots/fisher.py` makes the example plot (shown in
+exercises.pdf, fig. 27) of the naïve projection vs Fisher projection.