diff --git a/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/02_discrete-rv.tex b/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/02_discrete-rv.tex
index a36dc29..b80f6ed 100644
--- a/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/02_discrete-rv.tex
+++ b/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/02_discrete-rv.tex
@@ -14,5 +14,5 @@
 
 
 \subsubsection{Zusammenhang Verteilung, Verteilungsfunktion}
-\shorttheorem $\cX$ disk. Z.V. wie oben, dann ist Verteilungsfunktion: $\forall x \in \R \; F_\cX(x) = \sum_{\elementstack{y \in W}{y \leq x}} p(y)$.
+\shorttheorem $\cX$ disk. Z.V. wie oben, dann ist \hl{Verteilungsfunktion}: $\forall x \in \R \; F_\cX(x) = \sum_{\elementstack{y \in W}{y \leq x}} p(y)$.
 \textbf{Umgekehrt:} $p(x)$ ist die ``Sprunghöhe'' im Punkt $x \in W$, $W$ pos. Sprünge in $F_\cX$
diff --git a/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/03_distributions/01_geom.tex b/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/03_distributions/01_geom.tex
index 69e2294..aa5d902 100644
--- a/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/03_distributions/01_geom.tex
+++ b/semester4/ps/ps-jh/parts/02_discrete-continuous-rv/03_distributions/01_geom.tex
@@ -2,7 +2,9 @@
 {\scriptsize Warten auf den ersten Erfolg (in $\8$ Folge von Bernoulli-Experimenten)}
 
 \shortdefinition $\cX \sim \text{Geom}(p)$ mit $W = \N \backslash \{0\}$ falls $\forall k \in W$\\
-$\P[\cX = k] = \P[\cX > (k - 1)] \cdot p$ mit $\P[\cX > k] = (1 - p)^{k}$
+$\P[\cX = k] = (1 - p)^{k - 1} p$
+
+\shortremark[Verteilung] $F_\cX(k) = 1 - (1 - p)^k$
 
 \shortremark $\P[\cX = 1] = p$, da wir Konvetion $a^0 = 1$ verwenden.
 
diff --git a/semester4/ps/ps-jh/parts/03_expected-value/05_variance.tex b/semester4/ps/ps-jh/parts/03_expected-value/05_variance.tex
index 5989366..d99d0ea 100644
--- a/semester4/ps/ps-jh/parts/03_expected-value/05_variance.tex
+++ b/semester4/ps/ps-jh/parts/03_expected-value/05_variance.tex
@@ -26,5 +26,7 @@ Falls $\cX_k$ abhängig, dann gilt $\neq$
     \item $\cX \sim \text{H}(n, r, m)$, $\V[\cX] = m\frac{rn - r^2}{n^2} \frac{n - m}{n - 1}$
     \item $\cX \sim \text{Poisson}(\lambda)$, $\V[\cX] = \lambda = \E[\cX]$
     \item $\cX \sim \cU([a, b])$, $\V[\cX] = \frac{(b - a)^2}{12}$
+    \item $\cX \sim \text{Exp}(\lambda)$, $\V[\cX] = \frac{1}{\lambda^2}$
     \item $\cX \sim \cN(\mu, \sigma^2)$, $\V[\cX] = \sigma^2$
+    \item $\cX \sim \text{Cauchy}(x_0, \gamma)$: Existiert nicht
 \end{itemize}
diff --git a/semester4/ps/ps-jh/probability-and-statistics-cheatsheet.pdf b/semester4/ps/ps-jh/probability-and-statistics-cheatsheet.pdf
index 8daf9ef..77c9e89 100644
Binary files a/semester4/ps/ps-jh/probability-and-statistics-cheatsheet.pdf and b/semester4/ps/ps-jh/probability-and-statistics-cheatsheet.pdf differ