The distorting effect of deciding to stop sampling


People usually collect information to serve specific goals and often end up with samples that are unrepresentative of the underlying population. This can introduce biases on later judgments that generalize from these samples. Here we show that goals influence not only what information we collect, but also when we decide to terminate search. Using an optimal stopping analysis, we demonstrate that even when learners have no control over the content of a sample (i.e., natural sampling), the simple decision of when to stop sampling can yield sample distributions that are non-representative and could potentially bias future decision making. We test the prediction of these theoretical analyses with two behavioral experiments.

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