For this lesson, we will consider two method of graphical model assessment for repeated measurements, Q-Q plots and predictive ECDFs. We will also briefly revisit what we have done so far, the less-effective and soon-to-be-jettisoned method or plotting the CDF of the generative model parametrized by the MLE along with the ECDF. I note that we will not go over the implementation of these in Python here, but will rather cover the procedure and look at example plots. We will cover how to implement these methods in Python in the next lesson.
To have data sets in mind, we will revisit the data set from when we learned about the effects of neonicotinoid pesticides on bee sperm counts (Straub, et al., 2016). We considered the quantity of alive sperm in drone bees treated with pesticide and those that were not.