How to tell when Association might be Causation
The most important decisions we make, as individuals and collectively, are based on our perceptions of answers to causal questions. The cacophony of conflicting claims about the effects of diets, drugs, social and economic policies, are largely the result of the fact that, for most causal questions, we only have observational evidence. As statisticians, we have a unique appreciation of the issues involved with causal inference and we can help improve the public understanding of causality by helping students in our service courses to develop the judgment to assess causal claims. The talk will discuss some attempts to achieve this.
Date and Time:
Tuesday, June 13, 2017 - 11:05 to 11:50
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