The rationality of illusory correlation

Files in This Item:
File Description SizeFormat 
illusory_correlation_preprint.pdf307.53 kBAdobe PDFDownload
Title: The rationality of illusory correlation
Authors: Costello, FintanWatts, Paul
Permanent link: http://hdl.handle.net/10197/12114
Date: 1-Apr-2019
Online since: 2021-04-22T15:06:39Z
Abstract: When presented with 2 samples (a smaller sample from a Minority population and a larger sample from a Majority population), where some rare or frequent features occur at exactly the same rate in both samples, people reliably associate the rare feature with the Minority population and the frequent feature with the Majority population. This pattern is referred to as "illusory correlation," reflecting the standard assumption that such associations are fundamentally irrational. In this article we show that this assumption is incorrect, and demonstrate that this pattern of association linking rare features with the Minority and frequent features with the Majority (given a sample where those features occurred at the same proportion in both categories, and no further information) is in fact correct and follows a result in epistemic probability theory known as the "Rule of Succession." Building on this result, we present a new computational model of frequency-based illusory correlation, based on the Rule of Succession. We also discuss the implications of the Rule of Succession for our understanding of various other cognitive biases.
Type of material: Journal Article
Publisher: American Psychological Association
Journal: Psychological Review
Volume: 126
Issue: 3
Start page: 437
End page: 450
Copyright (published version): 2019 American Psychological Association
Keywords: HumansProbabilityAssociationThinkingProbability TheoryAdult
DOI: 10.1037/rev0000130
Language: en
Status of Item: Peer reviewed
ISSN: 0033-295X
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection

Show full item record

Page view(s)

123
Last Week
15
Last month
checked on May 10, 2021

Download(s)

9
checked on May 10, 2021

Google ScholarTM

Check

Altmetric


If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.