In which you will produce (and solve) a tutorial of your own.
This is your opportunity to apply what you've learned in a new context, or explore beyond the scope of the existing notes/tutorials, without the prescribed "walkthrough" format of a (previously written) tutorial. There's a wide landscape of possible design-your-own tutorials (DYOTs), and no absolutely fixed requirements. However, ideas must be approved in advance to make sure that the content and scope are within reason; this will be accomplished through an "assignment" on the course's Canvas site. Try to be as specific as possible regarding what you will actually do in the notebook, though of course this proposal is not binding and we can iterate.
At the simpler end, you might find a data set and a model to fit to it in the scientific literature, constrain the posterior distribution of the model parameters, find credible regions, and assess the goodness of fit as usual... all without straying beyond the methodology we've already covered. Provided that the solution is not too duplicative of a tutorial that already exists, this would be fine.
DYOTs could, however, also explore new methodology, either something we've covered in the notes but not provided tutorials on, or something entirely new.
Rarely, a DYOT might focus primarily on exposition of a new topic (i.e. resemble notes more than a tutorial), although thre still must be an analysis/demonstration component.
While we encourage the use of real data when possible, it should still be possible for us to run your completed notebooks, ideally in less than a minute or so, as usual. This might mean using "realistic" rather than real data, or simplified models, to avoid incorporating non-standard software, giant/complex data sets and/or computationally slow model evaluations. While there is definitely value in struggling with such things, we have found that doing so in the context of a class project is too much of a distraction from the core content of the course.
Note that you are being asked to define and solve a new problem here - not to actually produce a new tutorial. That is, you should not "withhold" code from your solution, as we so charmingly do.
In addition to producing the notebook, you (or your group jointly) will be asked to briefly and informally walk the class through the problem and its solution during the last week of class.
Of course, one way to get inspired is to look at papers in your field - lots of them probably present data and fit models to them! You can also work on something related to your own research. Please do not use proprietary data, however. The analysis must be original only in the sense that you have not done it before (though, even then, you might have already done it using methods other than the ones we cover in this class).
Alternatively, we might point out that there are several concepts and methods covered in the "Practice"-section notes that lack attached tutorials.
As always, collaboration is allowed and encouraged. In this case, a group effort should involve a well defined group identified at the idea-pitch stage, rather than occasional, casual collaboration, as might be the case for other tutorials. Such submissions should be done as an official "DYOT group" on Canvas, which you should be able to join in the "People" section.
Generally, you should aim to produce a notebook that, if it were made into a tutorial for others, would take around the same amount of time to solve as the existing ones (within the range, anyway). You will probably find that creating such a thing from scratch takes significantly more time than solving one that already exists. Depending on how involved a DYOT is and how many collaborators contribute to it, we may award more than 1 tutorial-equivalent of credit. Determining this, and preventing scope-creep, is one of the reasons for requiring pre-approval of DYOT ideas. The DYOT, as an optional replacement for the formal final project, is a new innovation in this class, so we'll be figuring out the typical level of effort/credit as we go.
Multiple DYOTs can also be completed for credit towards one's optional "Practice"-level tutorials.