Is probability matching smart? Associations between probabilistic choices and cognitive ability

Abstract

In three experiments involving over 1,500 university students (n 5 1,557) and two different probabilistic choice tasks, we found that the utility-maximizing strategy of choosing the most probable alternative was not the majority response. In a story problem version of a probabilistic choice task in which participants chose from among five different strategies, the maximizing response and the probabilitymatching response were each selected by a similar number of students (roughly 35% of the sample selected each). In a more continuous, or trial-by-trial,task, the utility-maximizing response was chosen by only one half as many students as the probability-matching response. More important, in both versions of the task, the participants preferring the utility-maximizing response were significantly higher in cognitive ability than were the participants showing a probability-matching tendency. Critiques of the traditional interpretation of probability matching as nonoptimal may well help explain why some humans are drawn to the nonmaximizing behavior of probability matching, but the traditional heuristics and biases interpretation can most easily accommodate the finding that participants high in computational ability are more likely to carry out the rule-based cognitive procedures that lead to maximizing behavior.

Insight and strategy in multiple-cue learning.

“…In contrast, the multi-match strategy would predict rain 78% of the time and fine 22% of the time. Evidence from a wide range of probabilistic tasks suggests that people often adopt such a matching strategy, even when it is not optimal (e.g., Shanks, Tunney, & McCarthy, 2002;Tversky & Edwards, 1966;West & Stanovich, 2003).…”

Betting on Illusory Patterns: Probability Matching in Habitual Gamblers

“…Koehler and James (2010), for instance, showed that even people who adopted probability matching endorsed maximizing as the better strategy when asked to directly compare the two, and used it more when it was brought to their attention before the task. Also, studies have shown that the maximizing strategy is used more often by students with greater academic experience (Gal and Baron 1996), higher college admission test scores (West and Stanovich 2003), higher working memory capacity (Rakow et al 2010), and higher cognitive reflection task scores (Koehler and James 2010), suggesting that education and cognitive capacity play a role in enhancing the use of a maximizing strategy.…”

“….25 9 .25). Probability matching is highly persistent (Healy and Kubovy 1981;Shanks et al 2002;for reviews, see Myers 1976;Vulkan 2000), even in tasks in which participants did not have to learn the outcome probabilities but were presented with a full description of outcomes and their probability (Gal and Baron 1996;Koehler and James 2009;Newell et al 2013;Newell and Rakow 2007;West and Stanovich 2003).…”

Probability matching in risky choice: The interplay of feedback and strategy availability

“…(See Newell, Lagnado, &Shanks, 2007, chap.11, andShanks etal., 2002, for further discussion. ) have investigated probability matching in tasks in which the outcomes and their probabilities of occurrence are fully described to participants (e.g., Gal & Baron, 1996;James & Koehler, 2011;Koehler & James, 2009, 2010Newell & Rakow, 2007;West & Stanovich, 2003). The finding that probability matching is common even in these situations is remarkable, given that the described problems provide all of the information necessary for rational responding (i.e., identification of the maximizing strategy as optimal), even before a single choice is made.…”