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In the lab students work in teams of 3--4. These teams, which persist throughout the semester, are assigned during the second week based on responses to an online questionnaire using the \catme\ \verb|Team-Maker| tool \cite{Layton_2010}.  A fraction of the lab grade is determined by peer and self assessment, using \catme\ \citep{Loughry_2007,Ohland_2012,Loughry_2014} and by participation, as observed by the instructor. The students periodically receive a link to a \catme\ peer evaluation form, in which they assess their team's work on recent labs. The goals of this peer assessment are 1) to stress the importance of being a patient, generous, and hard-working collaborator; 2) to think critically about one's own work and to measure that work against one's own expectations; and 3) to encourage all team members to contribute equally.  \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 currently have the students install a virtual machine (using \href{https://www.virtualbox.org/}{VirtualBox}) running Ubuntu Linux. Given the widespread availability of \ipython, we will likely drop the usage of virtual machines in subsequent editions of this course.}  Figure~\ref{f.sample-datasets} illustrates an in-class \ipython\ exercise that was used to illustrate the $\chi^2$-test. The students use the notebook to generate fake datsets, compute $\chi^2$ for those datasets, and then answer questions about their findings. When finished, the students upload their \ipython\ notebooks to a course dropbox for grading.