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[statistics] fixed pagebreaks

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Jan Benda 2019-11-25 23:18:29 +01:00
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statistics/lecture/statistics.tex
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@ -292,7 +292,6 @@ deviation $\sigma$.
The factor in front of the exponential function ensures the normalization to The factor in front of the exponential function ensures the normalization to
$\int p_g(x) \, dx = 1$, \eqnref{pdfnorm}. $\int p_g(x) \, dx = 1$, \eqnref{pdfnorm}.
\newpage
\begin{exercise}{gaussianpdf.m}{gaussianpdf.out} \begin{exercise}{gaussianpdf.m}{gaussianpdf.out}
\begin{enumerate} \begin{enumerate}
\item Plot the probability density of the normal distribution $p_g(x)$. \item Plot the probability density of the normal distribution $p_g(x)$.
@ -305,7 +304,6 @@ $\int p_g(x) \, dx = 1$, \eqnref{pdfnorm}.
\end{enumerate} \end{enumerate}
\end{exercise} \end{exercise}
\newpage
Histograms of real valued data depend on both the number of data Histograms of real valued data depend on both the number of data
values \emph{and} the chosen bin width. As in the example with the die values \emph{and} the chosen bin width. As in the example with the die
(\figref{diehistogramsfig} left), the height of the histogram gets (\figref{diehistogramsfig} left), the height of the histogram gets
@ -349,13 +347,11 @@ probability density functions like the one of the normal distribution
normal distributions (blue).} normal distributions (blue).}
\end{figure} \end{figure}
\newpage
\begin{exercise}{gaussianbinsnorm.m}{} \begin{exercise}{gaussianbinsnorm.m}{}
Normalize the histogram of the previous exercise to a probability density. Normalize the histogram of the previous exercise to a probability density.
\end{exercise} \end{exercise}
\newpage
\subsection{Kernel densities} \subsection{Kernel densities}
A problem of using histograms for estimating probability densities is A problem of using histograms for estimating probability densities is