By Ciaran Evans, Alex Reinhart, Philipp Burckhardt, Rebecca Nugent, & Gordon Weinberg (Carnegie Mellon University)
Abstract
Introductory statistics students find it notoriously difficult to reason about correlation and causation: when does correlation imply causation, and when does it not? Through think-aloud interviews with students and assessment results, we have seen that while they often recognize that correlation does not necessarily imply causation, they usually fail to understand why. To aid student understanding, we introduce a new activity to our introductory statistics labs that explores correlation vs. causation through simple causal diagrams. In this poster, we present preliminary results from this lab activity and some insights from our think-aloud research, to gain insight into how students think about this fundamental statistical concept.