human
Here the data represent (and had a quick look at them), what feature in the data do you want your model to explain well given the following:
1. Pre-registering a Test Statistic
The hypothesis we will test in this tutorial is the model outlined in the next section - but how well that model fits the data is a question we will answer in part using a test statistic. 
Having understood what the data represent (and had a quick look at them), what feature in the data do you want your model to explain well?  
With this in mind, what is a good test statistic to summarize the data? Spend a few mins thinking about this and discussing it, then implement is before moving on. You'll then use this "pre-registered" test statistic in a Bayesian model check below.
Your test statistic should be a function of the data only, although in general it's also possible to use statistics that are functions of both the data and model.
assistant
#Here the data represent (and had a quick look at them), what feature in the data do you want your model to explain well.
try:
    exec(open('solutions/teststatistic.py').read())
except IOError:
    REMOVE_THIS_LINE()
    def T(yy):
        """
        Argument: a data vector (either the real data or a simulated data set)
        Returns: a scalar test statistic computed from the argument
        """
        REPLACE_WITH_YOUR_SOLUTION()