Part 5: How do you prepare the data? · Module 10
The dataset we'll carry through the course
The Supportive-Supervision Dataset
Picture your supervision teams visiting six facilities and recording, for each one, whether four things were missing or broken, plus whether coverage was low. Everything is crisp-set: 1 means yes, 0 means no. Because we're in problem-solving mode, our conditions are framed as gaps , and the outcome is LowCov , where 1 means coverage fell below target.
Look at every facility where coverage was low. In each one, either the cold chain was broken (NoCold) or supervision was missing (NoSuper), and sometimes both. Now look at the two facilities that were fine: neither problem was present. Notice that NoTrain and NoComm show up on both sides, so they're red herrings. Hold that thought, because CNA is about to back up your detective work.
What You Will Be Able to Do
- Read a crisp-set supervision dataset row by row.
- Spot, by eye, which conditions separate the outcomes.
- Describe how each facility becomes one case.