Commit d2786e79 authored by Philipp Arras's avatar Philipp Arras
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Fixup

parent a17bc91e
Pipeline #109734 passed with stage
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......@@ -66,7 +66,7 @@ Bayesian reconstruction algorithms may be viewed in terms of three basic buildin
It contains the data, the statistics of the data including the error bars and a description of the measurement device itself.
\item The \emph{prior} $\mathcal P(s)$ describes the knowledge the scientist has \emph{before} executing the experiment.
In order to define a prior one needs to make one's knowledge about the physical process which was observed by the measurement device explicit.
\item Finally, one needs an algorithmic and computational framework which is able to actually do the Bayesian inference, compute the \emph{posterior} $\mathcal P(s/d)$, given the above information.
\item Finally, one needs an algorithmic and computational framework which is able to actually do the Bayesian inference, compute the \emph{posterior} $\mathcal P(s|d)$, given the above information.
\end{enumerate}
It becomes clear that these three parts are separate from each other.
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