Distinguishing between cause and effect
Joris M. Mooij, Dominik Janzing · 2008
We describe eight data sets that together formed the CauseEffectPairs task in the Causal-ity Challenge #2: Pot-Luck competition. Each set consists of a sample of a pair of sta-tistically dependent random variables. One variable is known to cause the other one, but this information was hidden from the participants; the task was to identify which of the two variables was the cause and which one the effect, based upon the observed sample. The data sets were chosen such that we expect common agreement on the ground truth. Even though part of the statistical dependences may also be due to hidden common causes, common sense tells us that there is a significant cause-effect relation between the two vari-ables in each pair. We also present baseline results using three different causal inference methods.