diff --git a/is/ub7/is7.pdf b/is/ub7/is7.pdf
index 5812b16..c2f1820 100644
--- a/is/ub7/is7.pdf
+++ b/is/ub7/is7.pdf
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diff --git a/is/ub7/is7.tex b/is/ub7/is7.tex
index 49305ec..81f9e0b 100644
--- a/is/ub7/is7.tex
+++ b/is/ub7/is7.tex
@@ -74,8 +74,6 @@
     \textbf{Exercise \arabic{n}: #1} (#2 Points)\\}
 
 
-
-
 \begin{document}
     %\header{BlattNr}{Tutor}{Abgabedatum}{Vorlesungsname}{Namen}{Semester}{Anzahl Aufgaben}
     \header{7}{}{2015-06-25}{Intelligent Systems I}{\textit{Maximus Mutschler}\\ \textit{Jan-Peter Hohloch}
@@ -97,14 +95,19 @@
                 \draw (Y) -- (W);
                 \draw (Z) -- (W);
             \end{tikzpicture}
-            \item %TODO
+            \item \includegraphics[width=.8\textwidth]{xw.png}
         \end{enumerate}
     \Aufgabe{Causal effects}{60}
         \begin{enumerate}[(a)]
-            \item TODO%TODO plot
+            \item see above
             \item Setting $\alpha$ to $0$ makes Z independent of X.\\
                 Z is just random noise ($N_z$), so it is independent of X\qed
-            \item %TODO
+            \item \begin{align*}
+                \frac{d}{dx}\mathds{E}\left(W|do\ X=x\right)&=-4\frac{d\mathds{E}(V|do\ X=x)}{dx}+0.5\frac{d\mathds{E}(Y|do\ X=x)}{dx}+2\frac{d\mathds{E}(Z|do\ X=x)}{dx}\\
+                &=0.5\cdot\left(-1\right)+2\cdot\alpha\\
+                &=2\alpha -0.5
+            \end{align*}
+            This is the slope of $W(x)$, which is only depending on $\alpha$.
         \end{enumerate}
 \end{document}
 
diff --git a/is/ub7/plotting.py b/is/ub7/plotting.py
new file mode 100755
index 0000000..2a79c70
--- /dev/null
+++ b/is/ub7/plotting.py
@@ -0,0 +1,40 @@
+#!/usr/bin/python3
+import numpy as np
+import random as rand
+import matplotlib.pyplot as plt
+
+n=1000
+alpha=np.arange(-2,2,0.1)
+
+V=[]
+W=[]
+X=[]
+Y=[]
+Z=[]
+
+for i in range(n):
+    V.append(rand.gauss(0,1))
+    X.append(3*V[i]+rand.gauss(0,1))
+    Y.append(-X[i]+rand.gauss(0,1))
+    Z.append(-alpha[0]*X[i]+rand.gauss(0,1))
+    W.append(-4*V[i]+0.5*Y[i]+2*Z[i]+rand.gauss(0,1))
+
+plt.plot(X,W,'x')
+#plt.show()
+
+
+#for a in alpha:
+V=[]
+W=[]
+X=[]
+Y=[]
+Z=[]
+for i in range(n):
+    V.append(rand.gauss(0,1))
+    X.append(3)
+    Y.append(-X[i]+rand.gauss(0,1))
+    Z.append(-alpha[0]*X[i]+rand.gauss(0,1))
+    W.append(-4*V[i]+0.5*Y[i]+2*Z[i]+rand.gauss(0,1))
+plt.plot(X,W,'x')
+
+plt.show()
diff --git a/is/ub7/xw.png b/is/ub7/xw.png
new file mode 100644
index 0000000..8dee372
--- /dev/null
+++ b/is/ub7/xw.png
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