The psychology of the Monty Hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser.

Krauss, Stefan; Wang, Xiao-Tian

doi:10.1037/0096-3445.132.1.3

Cited by 86 publications

(135 citation statements)

References 25 publications

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“…Fractions are hard to understand whereas collections seem to be easy (Brase, Cosmides, & Tooby, 1998), as illustrated by the almost universal use of fi ngers as a representational system (Butterworth, 1999(Butterworth, , 2001, and brain imaging studies suggest that key number areas are closely connected to the fi nger circuit (Dehaene, Spelke, Pinel, Stanescu, & Tviskin, 1999). Krauss and Wang (2003) studied the notorious Monty Hall problem, which most adults fail at, and showed that correct answers can be facilitated by changing the single-event question ("should I switch or not switch doors") into a frequency question ("in how many cases will switching win? "), and Krauss and Atmaca (2004) showed similar facilitation for children and adolescents aged 11 to 19.…”

Section: Resultsmentioning

confidence: 99%

Children can solve Bayesian problems: the role of representation in mental computation

2006

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Abstract. Can children reason the Bayesian way? We argue that the answer to this question depends on how numbers are represented, because a representation can do part of the computation. We test, for the fi rst time, whether Bayesian reasoning can be elicited in children by means of natural frequencies. We show that when information was presented to fourth, fi fth, and sixth graders in terms of probabilities, their ability to estimate the Bayesian posterior probability was zero. Yet when the same information was presented in natural frequencies, Bayesian reasoning showed a steady increase from fourth to sixth grade, reaching an average level of 19%, 39%, and 53%, respectively, in two studies. Sixth graders' performance with natural frequencies matched the performance of adults with probabilities. But this general increase was accompanied by striking individual diff erences. More than half of the sixth graders solved most or all problems, whereas one third could not solve a single one. An analysis of the children's responses provides evidence for the use of three non-Bayesian strategies. Th ese follow an overlapping wave model of development and continue to be observed in the minds of adults. More so than adults' probabilistic reasoning, children's reasoning depends on a proper representation of information.

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Section: Resultsmentioning

confidence: 99%

Children can solve Bayesian problems: the role of representation in mental computation

2006

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“…Unfortunately, it is often possible for an incorrect answer to be justified. Probability calculations are frequently counterintuitive, and groups may adopt socially plausible but inappropriate strategies This phenomenon is illustrated by the history of the Monty Hall problem, where incorrect solutions are frequently more persuasive than correct solutions (Krauss & T, 2003).…”

Section: Allowing Experts To Interact Is Possibly a Good Ideamentioning

confidence: 99%

Forecasts or fortune-telling: When are expert judgements of safety risk valid?

Rae

Alexander

2017

Safety Science

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“…Then you are asked if you want to keep your first choice or switch to the third choice, before seeing what is under both. The correct decision is to switch, because you double your odds of winning (Selvin, 1975), but few people appreciate why that has to be true (Krauss & Wang, 2003). More often, people will stick with their first choice because they are afraid to find out they were right but then switched (Burns & Wieth, 2004;Gilovich, Medvec, & Chen, 1995), or they will switch (or stay) because they say it no longer matters, and the odds are 50:50 for winning.…”

Section: The Monty Hall Problem and Misrepresenting Probabilitymentioning

confidence: 99%

To Err Is (Not Only) Human: Fallibility as a Window Into Primate Cognition

Beran¹

2017

CCBR

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Human cognition affords our species an excellent toolbox for solving problems. Many nonhuman animal species appear to share with humans some of these tools. However, human cognition also is fallible. Susceptibility to perceptual illusions, misrepresentation of probabilities, cognitive biases, faulty memory, and heuristics all present sources of error from which behavior is suboptimal in the pursuit of goals. Some nonhuman species share these perceptual and cognitive biases with humans. Examples of this are described for nonhuman primates, ranging from perceptual illusions to humanlike failures on games of probability such as the Monty Hall Problem. Sometimes the performances of nonhuman primates mirror those of humans, but there are exceptions. Given that other species do experience things erroneously and make errors in judgment, it is an exciting question of whether they also might generate any strategies to offset their fallibility. Two examples to suggest that they do are provided from research with chimpanzees. One is of strategic self-distraction in the face of tempting rewards in a delay of gratification task. The other is of information-seeking behaviors in different contexts where chimpanzees have different types of information. This research, and that of many other groups, shows the value of examining perceptual and cognitive errors across species, and how different individuals and different species may be equipped psychologically to deal with the possibility of these errors occurring. Keywords: primate cognition, perception, illusions, self-control, metacognition IntroductionThe 20th century saw a shift in how humans thought about nonhuman animals (hereafter, animals), their behavior, and the cognitive processes that might underlie their behavior. Comparative cognition emerged as a strong discipline in the second half of the century, largely as a result of the broader cognitive revolution in human psychology, continued developments in ethology, and new opportunities to study a diverse range of species (Shettleworth, 2010). Earlier comparative psychologists certainly took an interest in aspects of cognition (see Dewsbury, 1984Dewsbury, , 2000Dewsbury, , 2013, but researchers in the second half of the century provided new approaches to understanding animal minds. Initially these approaches focused largely on traditional aspects of human cognitive psychology, including memory, perceptual capacities, and learning phenomenon (e.g., Honig & Fetterman, 1992;Hulse, Fowler, & Honig, 1978;Roitblat, Bever, & Terrace, 1984), as they might reflect the use of mental representations and other information-processing approaches for interacting with the world. Later, 58COMPARATIVE COGNITION & BEHAVIOR REVIEWS Beran research increasingly focused on questions that covered nearly every topic found in a human cognitive psychology textbook, and even questions that were not typically discussed in such sources (e.g., theory of mind, deception, mind reading, cooperative decision making, metacognition, mental time travel, and ot...

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The psychology of the Monty Hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser.

Cited by 86 publications

References 25 publications

Children can solve Bayesian problems: the role of representation in mental computation

Children can solve Bayesian problems: the role of representation in mental computation

Forecasts or fortune-telling: When are expert judgements of safety risk valid?

To Err Is (Not Only) Human: Fallibility as a Window Into Primate Cognition

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