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\subsection{Introduction of numerical analysis}  Students are expected to do their lab work using \ipython\ notebooks. There are several reasons for adopting \texttt{Python}: it is widely used in astronomy and other STEM disciplines; it is easy to learn but supports complex programming; it has powerful libraries---\np, \sp, and \plt---for numerical analysis and plotting; and the \ipython\ notebooks are relatively platform-independent.\footnote{To ensure a standard working environment, we require the students to install (using \href{https://www.virtualbox.org/}{VirtualBox}) a virtual machine running Ubuntu Linux with the Anaconda Python distribution. Given the broad cross-platform distribution of Anaconda Python, we may drop the usage of virtual machines in subsequent editions of this course.}  Figure~\ref{fig:sample-datasets} illustrates an in-class exercise, using an \ipython\ notebook, on the $\chi^2$-test. The students use the notebook to generate fake datsets, to compute $\chi^2$ for those datasets, and then to answer questions about their findings. When finished, the students upload their notebooks to a course dropbox for grading. To try the notebook, move the cursor over the figure and click on the \verb|Launch ipython| link that appears below the figure.