This showcase documents a preprocessing pipeline for heart-transplant data where domain constraints and data-quality issues matter as much as the final model. The point is not only to clean the data, but to expose the assumptions that shape downstream analyses.
I use this project as an example of the kind of applied statistical work I enjoy most: making messy, consequential data more usable without hiding the judgment calls embedded in the workflow.