Being paid relatively well most of the time: Negatively skewed payments are more satisfying.

How does the structure of a series of payments influence its recipient's satisfaction? A common hypothesis is that each payment will be compared with a single "standard" or "reference" payment (e.g., the average payment). Cognitive models of judgment such as range frequency theory predict in contrast that the entire payment distribution will influence evaluation of each individual payment. Two experiments examined satisfaction with a series of payments. In both experiments, most payments were either relatively high in the experienced distribution (the distribution was negatively skewed) or relatively low (positively skewed). The total and average payment was held constant. Experiment 1 found that average satisfaction with individual payments was higher when the payments were negatively skewed, consistent with range frequency theory, and earlier findings were extended by comparing range frequency theory with a range-based model, a rank-based model, and a reference point model at the individual level. Experiment 2 examined satisfaction with whole sequences of payments and found that receiving a negatively skewed sequence was more satisfying overall than receiving a positively skewed sequence. It is concluded that negatively skewed payment distributions are more satisfying, as predicted by cognitive models of judgment.

A dilution effect without dilution: When missing evidence, not non-diagnostic evidence, is judged inaccurately.

When asked to combine two pieces of evidence, one diagnostic and one non-diagnostic, people show a dilution effect: the addition of non-diagnostic evidence dilutes the overall strength of the evidence. This non-normative effect has been found in a variety of tasks and has been taken as evidence that people inappropriately combine information. In a series of five experiments, we found the dilution effect, but surprisingly it was not due to the inaccurate combination of diagnostic and non-diagnostic information. Because we have objectively correct answers for our task, we could see that participants were relatively accurate in judging diagnostic evidence combined with non-diagnostic evidence, but overestimated the strength of diagnostic evidence alone. This meant that the dilution effect - the gap between diagnostic evidence alone and diagnostic evidence combined with non-diagnostic evidence - was not caused by dilution. We hypothesized that participants were filling in "missing" evidence in a biased fashion when presented with diagnostic evidence alone. This hypothesis best explained the experimental results.