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Covariance is bilinear
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Signed-off-by: Thomas Gassmann <[email protected]>
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thomasgassmann committed Jul 5, 2023
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Expand Up @@ -438,10 +438,10 @@ \subsection{Varianz}
\end{enumerate}

\subsection{Kovarianz}
\begin{subbox}{Definition Kovarianz}
\begin{subbox}{}
Wenn \(X, Y\) zwei ZV mit \(\E[X^2] < \infty, \E[Y^2] < \infty\), dann ist die Kovarianz zwischen \(X, Y\) definiert als
\[\text{Cov}(X,Y) = \E[X \cdot Y] - \E[X] \cdot \E[Y]\]
Falls $\text{Cov}(X,Y) = 0$ nennt man $X, Y$ unkorreliert.
Falls $\text{Cov}(X,Y) = 0$ nennt man $X, Y$ unkorreliert. Die Kovarianz ist bilinear.
\end{subbox}
\begin{itemize}
\item \(\text{Cov}(X,X) = \sigma_X^2\)
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