How accurate are laypeople’s intuitions about probability distributions of events? The economic and psychological literatures provide opposing answers. A classical economic view assumes that ordinary decision makers consult perfect expectations, while recent psychological research has emphasized biases in perceptions. In this work, we test laypeople’s intuitions about probability distributions. To establish a ground truth against which accuracy can be assessed, we control the information seen by each subject to establish unambiguous normative answers. We find that laypeople’s statistical intuitions can be highly accurate, and depend strongly upon the elicitation method used. In particular, we find that eliciting an entire distribution from a respondent using a graphical interface, and then computing simple statistics (such as means, fractiles, and confidence intervals) on this distribution, leads to greater accuracy, on both the individual and aggregate level, than the standard method of asking about the same statistics directly.

We investigated the relations between numeracy and superior judgment and decision making in two large community outreach studies in Holland (n=5408). In these very highly educated samples (e.g., 30–50% held graduate degrees), the Berlin Numeracy Test was a robust predictor of financial, medical, and metacognitive task performance (i.e., lotteries, intertemporal choice, denominator neglect, and confidence judgments), independent of education, gender, age, and another numeracy assessment. Metacognitive processes partially mediated the link between numeracy and superior performance. More numerate participants performed better because they deliberated more during decision making and more accurately evaluated their judgments (e.g., less overconfidence). Results suggest that well-designed numeracy tests tend to be robust predictors of superior judgment and decision making because they simultaneously assess (1) mathematical competency and (2) metacognitive and self-regulated learning skills.

Glöckner and Bröder (2011) have shown that for 77.5% of their participants’ decision making behavior in decisions involving recognition information and explicitly provided additional cues could be better described by weighted-compensatory Parallel Constraint Satisfaction (PCS) Models than by non-compensatory strategies such as recognition heuristic (RH) or Take the Best (TTB). We investigate whether this predominance of PCS models also holds in memory-based decisions in which information retrieval is effortful and cognitively demanding. Decision strategies were analyzed using a maximum-likelihood strategy classification method, taking into account choices, response times and confidence ratings simultaneously. In contrast to the memory-based-RH hypothesis, results show that also in memory-based decisions for 62% of the participants behavior is best explained by a compensatory PCS model. There is, however, a slight increase in participants classified as users of the non-compensatory strategies RH and TTB (32%) compared to the previous study, mirroring other studies suggesting effects of costly retrieval.

One prominent model in the realm of memory-based judgments and decisions is the recognition heuristic. Under certain preconditions, it presumes that choices are based on recognition in a one-cue non-compensatory manner and that other information is ignored. This claim has been studied widely—and received, at best, mixed support—in probabilistic inferences. By contrast, only a small number of recent investigations have taken the RH to the realm of preferential decisions (i.e. consumer choice). So far, the conclusion has been that the RH cannot satisfactorily account for aggregate data patterns, but no fully specified alternative model has been demonstrated to provide a better account. Herein, the data from a recent consumer-choice study (Thoma & Williams, 2013) are re-analyzed with the outcome-based maximum-likelihood strategy classification method, thus testing several competing models on individual data. Results revealed that an alternative compensatory model (an equal weights strategy) accounted best for a larger number of datasets than the RH. Thereby, the findings further specify prior results and answer the call for comparative model testing on individual data that has been voiced repeatedly.

Are people honest about the extent to which they engage in unethical behaviors? We report an experiment examining the relation between self-reported risky unethical tendencies and actual dishonest behavior. Participants’ self-reported risk taking tendencies were assessed using the Domain-Specific Risk-Taking (DOSPERT) questionnaire, while actual self-serving dishonesty was assessed using a private coin tossing task. In this task, participants predicted the outcome of coin tosses, held the predictions in mind, and reported whether their predictions were correct. Thus, the task allowed participants to lie about whether their predictions were correct. We manipulated whether reporting higher correct scores increased (vs. not) participants monetary payoff. Results revealed a positive relation between self-reported unethical risky tendencies and actual dishonesty. The effect was limited to the condition in which dishonesty was self-serving. Our results suggest liars are aware of their dishonest tendencies and are potentially not ashamed of them.

Trolley problems have been used in the development of moral theory and the psychological study of moral judgments and behavior. Most of this research has focused on people from the West, with implicit assumptions that moral intuitions should generalize and that moral psychology is universal. However, cultural differences may be associated with differences in moral judgments and behavior. We operationalized a trolley problem in the laboratory, with economic incentives and real-life consequences, and compared British and Chinese samples on moral behavior and judgment. We found that Chinese participants were less willing to sacrifice one person to save five others, and less likely to consider such an action to be right. In a second study using three scenarios, including the standard scenario where lives are threatened by an on-coming train, fewer Chinese than British participants were willing to take action and sacrifice one to save five, and this cultural difference was more pronounced when the consequences were less severe than death.

Previous research has demonstrated that consumers’ decisions regarding supplementary pensions could be affected by biases. Bernatzi and Thaler’s experiment demonstrated that menu design can influence pension fund enrollment decisions, in that participants appear to adopt a naïve heuristic, i.e., “extremeness aversion”. Using a database of 27 occupational pension funds from 2007 to 2011, representing 1,732,530 employees, this study asked whether menu design affected Italian workers’ choices regarding the supplementary pension system as a result of the new rules enacted by the regulator in 2007. Most enrolled workers opted for the median investment line. I discuss the possible relevance of this result to public policy, in particular the possibility of including these preferences in the regulations, with the aim of benefiting employees.

Pie charts are often used to communicate risk, such as the risk of driving. In the foreground-background salience effect (FBSE), foreground (probability of bad event) has greater salience than background (no bad event) in such a chart. Experiment 1 confirmed that the displays format of pie charts showed a typical FBSE. Experiment 2 showed that the FBSE resulted from a difference in cognitive efforts in processing the messages and that a foreground-emphasizing display was easier to process. Experiment 3 manipulated subjects’ information processing mindset and explored the interaction between displays format and information processing mindset. In the default mindset, careless subjects displayed a typical FBSE, while those who were instructed to be careful reported similar risk-avoidant behavior preference reading both charts. Suggestions for improving risk communication are discussed.