Random variation and systematic biases in probability estimation
Bibliographic Data
| ID | 21307530 |
|---|---|
| Authors | Rita Howe (0000-0003-3397-8382, University College Dublin, corresponding author), Fintan Costello (0000-0002-3953-7863, University College Dublin) |
| Year | 2020 |
| Volume | 123 |
| Pages | 101306 |
| Publication date | 2020-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Cognitive Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0010-0285 • E-ISSN: 1095-5623 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.cogpsych.2020.101306 |
| PMID | 33189032 |
| OpenAlex | W3101713375 |
| Language | EN |
| Citations received | 4 |
| References cited | 49 |
A number of recent theories have suggested that the various systematic biases and fallacies seen in people's probabilistic reasoning may arise purely as a consequence of random variation in the reasoning process. The underlying argument, in these theories, is that random variation has systematic regressive effects, so producing the observed patterns of bias. These theories typically take this random variation as a given, and assume that the degree of random variation in probabilistic reasoning is sufficiently large to account for observed patterns of fallacy and bias; there has been very little research directly examining the character of random variation in people's probabilistic judgement. We describe 4 experiments investigating the degree, level, and characteristic properties of random variation in people's probability judgement. We show that the degree of variance is easily large enough to account for the occurrence of two central fallacies in probabilistic reasoning (the conjunction fallacy and the disjunction fallacy), and that level of variance is a reliable predictor of the occurrence of these fallacies. We also show that random variance in people's probabilistic judgement follows a particular mathematical model from frequentist probability theory: the binomial proportion distribution. This result supports a model in which people reason about probabilities in a way that follows frequentist probability theory but is subject to random variation or noise
Bayes' theorem · Bayesian inference · Bayesian probability · Econometrics · Epistemology · Fallacy · Frequentist inference · Frequentist probability · Judgement · Probabilistic logic · Statistics · Variance (accounting) · Variation (astronomy) · Bayesian Modeling and Causal Inference · Decision-Making and Behavioral Economics · Forecasting Techniques and Applications · Mathematics
Stan
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Explaining High Conjunction Fallacy Rates
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On the Importance of Random Error in the Study of Probability Judgment. Part I
Representativeness and conjoint probability
How alike is it versus how likely is it
Heuristic Decision Making
Toward a synthesis of cognitive biases
From Nudging to Budging
| Unique citing works | 4 |
|---|---|
| Citations per year | 2 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |