In the Data Science Games project, we started talking, early, about what we called data moves. We weren’t quite sure what they were exactly, but we recognized some when we did them.
In CODAP, for example (like in Fathom), there is this thing we learn to do where you select points in one graph and, since when you select data in CODAP, the data are selected everywhere, the same points are selected in all other graphs—and you can see patterns that were otherwise hidden.
You can use that same selection idea to hide the selected or unselected points, thereby filtering the data that you’re seeing. Anyway, that felt like a data move, a tool in our data toolbox. We could imagine pointing them out to students as a frequently-useful action to take.
I’ve mentioned the idea in a couple of posts because it seemed to me that data moves were characteristic of data science, or at least the proto-data-science that we have been trying to do: we use data moves to make sense of rich data where things can get confusing; we use data moves to help when we are awash in data. In traditional intro stats, you don’t need data moves because you generally are given exactly the data you need.