Calculate or wait: Is man an eager or a lazy intuitive statistician?

The role of episodic memory sampling in evaluation

Many models of choice assume that people retrieve memories of past experiences and use them to guide evaluation and choice. In this paper, we examine whether samples of recalled past experiences do indeed underpin our evaluations of options. We showed participants sequences of numerical values and asked them to recall as many of those values as possible and also to state how much they would be willing to pay for another draw from the sequence. Using Bayesian mixed effects modeling, we predicted participants' evaluation of the sequences at the group level from either the average of the values they recalled or the average of the values they saw. Contrary to the predictions of recall-based models, people's evaluations appear to be sensitive to information beyond what was actually recalled. Moreover, we did not find consistent evidence that memory for specific items is sufficient to predict evaluation of sequences. We discuss the implications for sampling models of memory and decision-making and alternative explanations.

Where did that come from?--Identifying the source of a sample

People's ability to summarize their knowledge of an observed numerical variable has been extensively studied. However, many real-life situations require people to go beyond summary statistics and infer which process or distribution has generated a sample. The present study investigates the extent to which people can make such inferences when the experienced variable is continuous and when they have had previous experience with instances of the variable. It also tests specific predictions derived from three possible cognitive processes of how inferences about a generating distribution are made. The results indicate that participants are efficient and flexible intuitive statisticians, requiring only as little as four observations in a sample to successfully infer which distribution it came from. Further, the results indicate that the cognitive process supporting the inference uses statistical properties of both an experienced distribution and a presented test sample, as suggested by the Naïve Sampling Model (NSM).