Distinguishing the Ratio Bias from Unsystematic Error

Situation and Individual‐difference Effects

Datos Bibliográficos

ID12165914
AutoresEric R Stone (0000-0002-1126-1391, Wake Forest University Winston‐Salem NC USA, autor de correspondencia), Andrew M Parker (0000-0001-7511-0894, RAND Corporation Pittsburgh PA USA, autor de correspondencia), Lauren Townsend (Wake Forest University), Lauren D Townsend (Wake Forest University Winston‐Salem NC USA)
Año2018
Volumen31
Número4
Páginas587-601
Fecha de publicación2018-01-23
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaJournal of Behavioral Decision Making (JOURNAL)
Identificadores de la revistaISSN: 0894-3257 • E-ISSN: 1099-0771
EditorialWiley (PUBLISHER • GB)
DOI10.1002/bdm.2068
OpenAlexW2790149479
IdiomaEN
Citas recibidas4
Referencias citadas46

People often perceive the occurrence of events to be less likely when the likelihood of the event is expressed in ratios consisting of smaller numbers versus larger numbers, an effect known as the ratio bias. This work presents a theoretical framework for the conditions that need to be met for the ratio bias to occur. In doing so, we contrast effects on the ratio bias to those on unsystematic error, which have often been confounded in previous research. We find that the ratio bias is weaker (1) when both sets of numbers are relatively large than when both sets of numbers are relatively small; (2) for scenarios involving lottery tickets than for scenarios involving drawing balls from a bin; and (3) when a physical display depicting the numbers is provided to participants. Each of these factors reduced the ratio bias without reducing unsystematic error. Additionally, we show that unsystematic error is lower among people who (1) reason on the basis of proportions rather than on the basis of the numerator and denominator individually; (2) score higher on the rational scale of the Rational–Experiential Inventory; and (3) are of higher numeracy. We use these results to distinguish causes of error generally from those on the ratio bias specifically and discuss the implications for our understanding of when the ratio bias occurs. Copyright © 2018 John Wiley & Sons, Ltd

Contrast (vision · Econometrics · Lottery · Statistics · Cognitive and developmental aspects of mathematical skills · Computer Science · Decision-Making and Behavioral Economics · Mathematics · Neural and Behavioral Psychology Studies · Psychology · Artificial Intelligence