diff --git a/projects/project_eod/eod.tex b/projects/project_eod/eod.tex
index 647a756..e225546 100644
--- a/projects/project_eod/eod.tex
+++ b/projects/project_eod/eod.tex
@@ -11,31 +11,38 @@
 
 
 %%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+Weakly electric fish employ their self-generated electric field for
+prey-capture, navigation and also communication. In many of these fish
+the {\em electric organ discharge} (EOD) is well described by a
+combination of a sine-wave and a few of its harmonics (integer
+multiples of the fundamental frequency).
 
 \begin{questions}
-  \question In the data file {\tt EOD\_data.mat} you find a time trace
-  and the {\em electric organ discharge (EOD)} of a weakly electric
-  fish {\em Apteronotus leptorhynchus}. 
+  \question In the data file {\tt EOD\_data.mat} you find two
+  variables. The first contains the time at which the EOD was sampled
+  and the second the acutal EOD recording of a weakly electric fisch
+  of the species {\em Apteronotus leptorhynchus}.
   \begin{parts}
-    \part Load and plot the data in an appropriate way. Time is in
-    seconds and the voltage is in mV/cm.
-    \part Fit the following curve to the eod (select a small time
-    window, containing only 2 or three electric organ discharges, for
+    \part Load the data and create a plot showing the data. Time is given in
+    seconds and the voltage is given in mV/cm.
+    \part Fit the following curve to the EOD (select a \textbf{small} time
+    window, containing only two or three electric organ discharges, for
     fitting, not the entire trace) using least squares:
     $$f_{\omega_0,b_0,\varphi_1, ...,\varphi_n}(t) = b_0 +
     \sum_{j=1}^n \alpha_j \cdot \sin(2\pi j\omega_0\cdot t + \varphi_j
-    ).$$ $\omega_0$ is called {\em fundamental frequency}. The single
+    ).$$ $\omega_0$ is called the {\em fundamental frequency}. The single
     terms $\alpha_j \cdot \sin(2\pi j\omega_0\cdot t + \varphi_j )$
-    are called {\em harmonic components}. The variables $\varphi_j$
+    are called the {\em harmonic components}. The variables $\varphi_j$
     are called {\em phases}, the $\alpha_j$ are the amplitudes. For
     the beginning choose $n=3$.
     \part Try different choices of $n$ and see how the fit
-    changes. Plot the fits and the original curve for different
-    choices of $n$. Also plot the fitting error as a function of
-    $n$. 
+    changes. Plot the fits and the section of the original curve that
+    you used for fitting for different choices of $n$. Also plot the
+    fitting error as a function of $n$.
+    \part Why does the fitting fail when you try to fit the entire recording?
     \part (optional) If you want you can also play the different fits
-    and the original as sound.
-    
+    and the original as sound (check the help).
+
   \end{parts}
 \end{questions}