Biased perception of distributions: Anchoring, interpolation and smoothing as potential causes

Abstract

Perceiving the degree of variation in the social and non-social environment is a cognitive task that is important for many judgments and decisions. In the present research, we investigated cognitive underpinnings of how people estimate the average value of segments of a statistical distribution (e.g., what is the average income of the richest 25% of a population?). In three experiments (total N = 222), participants learned about the values of experimentally created distributions of income values and city sizes and later estimated the mean value of the four quarters of values. We expected participants to draw on heuristic shortcuts to generate such judgments. More specifically, we hypothesized that participants use the endpoints of the distributions as anchors and determine the mean values by linear interpolation. In addition, we tested the contribution of three further processes (Range-Frequency adjustments, Normal Smoothing, Linear Smoothing). Quantitative model tests suggest that anchoring and Linear Smoothing both affected mean interquartile judgments. This conclusion is corroborated by tests of qualitative predictions of the models under consideration.