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presentations/causality-presentation: Added
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presentations/causality-presentation/backup/end.tex
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presentations/causality-presentation/backup/end.tex
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%!TEX root = interventions.tex
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\section{Ende}
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\subsection{Quellen}
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\begin{frame}{Quellen}
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\begin{itemize}
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\item \href{https://stat.ethz.ch/people/jopeters/index/edit/causalityHomepage/causality_files/scriptChapter1-4.pdf}{Causality, 2015. Jonas Peters.}
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\end{itemize}
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\end{frame}
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\begin{frame}{Definitionen}
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\begin{block}{Unabhängigkeit}
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$X$ und $Y$ sind unabhängig $:\Leftrightarrow p(x, y) = p(x) \cdot p(y) \;\;\;\forall x,y$.
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Man schreibt dann: $X \perp\!\!\!\perp Y$ und andernfalls $X \not\!\perp\!\!\!\perp Y$
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\end{block}
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\begin{block}{Korrelation}
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Seien $X$ und $Y$ Zufallsvariablen und
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\[C(X,Y) := \mathbb{E}((X- \mathbb{E}X) \cdot (Y - \mathbb{E}Y))\]
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die Kovarianz zwischen $X$ und $Y$. Gilt $C(X, Y) = 0$, so heißen
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$X$ und $Y$ unkorreliert.
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\end{block}
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\end{frame}
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