Abstract
AbstractThe processing of sequentially presented numerical information is a prerequisite for decisions from experience, where people learn about potential outcomes and their associated probabilities and then make choices between gambles. Little is known, however, about how people's preference for choosing a gamble is affected by how they perceive and process numerical information. To address this, we conducted a series of experiments wherein participants repeatedly sampled numbers from continuous outcome distributions. They were incentivized either to estimate the means of the numbers or to state their minimum selling prices to forgo a consequential draw from the distributions (i.e., the certainty equivalents or valuations). We found that participants valued distributions below their means, valued high‐variance sequences lower than low‐variance sequences, and valued left‐skewed sequences lower than right‐skewed sequences. Though less pronounced, similar patterns occurred in the mean estimation task where preferences should not play a role. These results are not consistent with prior findings in decision from experience such as the overweighting of high numbers and the underweighting of rare events. Rather, the qualitative effects, as well as the similarity of effects in valuation and estimation, are consistent with the assumption that people process numbers on a compressed mental number line in valuations from experience.
Highlights
In many real-world situations, people experience decision outcomes over time
Decision makers must integrate numerical information such as returns on investments that accrue sequentially. This scenario is modeled using the decisions from experience (DFEs) paradigm (Hertwig et al 2004; Barron & Erev, 2003; Weber et al 2004), where people can freely sample from an outcome distribution and afterward make a consequential choice
Under the assumption that participants were well calibrated to the mean estimation task, the variability of the monetary bonus should have been higher in the valuation than in the estimation task
Summary
Decision makers must integrate numerical information such as returns on investments that accrue sequentially In experimental research, this scenario is modeled using the decisions from experience (DFEs) paradigm (Hertwig et al 2004; Barron & Erev, 2003; Weber et al 2004), where people can freely sample from an outcome distribution and afterward make a consequential choice. This scenario is modeled using the decisions from experience (DFEs) paradigm (Hertwig et al 2004; Barron & Erev, 2003; Weber et al 2004), where people can freely sample from an outcome distribution and afterward make a consequential choice This contrasts with the decisions from description (DFD) paradigm, where all relevant information is readily summarized. The extent to which this could be the case in DFE, where understanding a choice option requires the perception, memorization, and integration of sequential numeric information, is an open question
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