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  \usecolortheme{crane}
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\AtBeginSection[]
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  \begin{frame}<beamer>
    \frametitle{Outline}
    \tableofcontents[currentsection]
  \end{frame}
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\author{Jordi G. H. $\langle$jordigh@octave.org$\rangle$ }


\title{The Medcouple}
\subtitle{A robust measure of skewness}
\date{}

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\begin{document}

\begin{frame}
  \titlepage
\end{frame}

\begin{frame}
  \frametitle{Outline}
  \tableofcontents
\end{frame}

\section{Outliers and Boxplots}

\begin{frame}
  What is an outlier?
\end{frame}

\begin{frame}
  \begin{center}
    \pgfimage[width=4.5in,height=3.5in]{img/boys-and-girls}
  \end{center}
\end{frame}

\section{The Medcouple}

\begin{frame}
  omg
\end{frame}


\begin{frame}
  \begin{center}
    \pgfimage[width=4in]{img/naive/x-orig.png}
  \end{center}

  Take some $X$ random numbers.
\end{frame}

\begin{frame}
  \begin{center}
    \pgfimage[width=4in]{img/naive/x-sorted.png}
  \end{center}

  Sort them.
\end{frame}

\begin{frame}
  \begin{center}
    \pgfimage[width=4in]{img/naive/sortx-red.png}
  \end{center}

  Pick the median.
\end{frame}

\begin{frame}
  \begin{overlayarea}{\textwidth}{8cm}
    \only<1>{%
      \begin{center}
        \pgfimage[height=2in]{img/naive/medc-computation-init.png}
      \end{center}
      Split up $X$ into $X^+$ and $X^-$ along the median.}
    \only<2>{%
      \begin{center}
        \pgfimage[height=2in]{img/naive/medc-computation.png}
      \end{center}
      Evaluate the kernel for all couples.
      \[
      \frac{ (x_i^+ - x_m) - (x_m - x_j^-)}{x_i - x_j},
      \quad x_i^+ \in X^+, \quad x_j^- \in X^-
      \]}
    \only<3>{%
      \begin{center}
        \pgfimage[height=2in]{img/naive/medc-computation-done.png}
      \end{center}
      The median of this matrix is the medcouple.}
  \end{overlayarea}
\end{frame}

\section{Computation of the Medcouple}

\begin{frame}
  wtf
\end{frame}

\end{document}