Kahneman and Tversky showed that when people make probability judgements, they tend to ignore relevant statistical information (e.g., sample size) and instead rely on a representativeness heuristic, whereby subjective probabilities are influenced by the degree to which a target is perceived as similar to (representative of) a typical example of the relevant population, class or category. Their article has become a cornerstone in many lines of research and has been used to account for various biases in judgement and decision-making. Despite the impact this article has had on theory and practice, there have been no direct replications. In a pre-registered experiment (N = 623; Amazon MTurk on CloudResearch), we conducted a replication and extensions of nine problems from Kahneman and Tversky’s 1972 article. We successfully replicated eight out of the nine problems. We extended the replication by examining the consistency of heuristic responses across problems and by examining decision style as a predictor of participants’ use of the representativeness heuristic. Materials, data, and code are available on: https://osf.io/nhqc4/
AgnoliF. (1991). Development of judgmental heuristics and logical reasoning: Training counteracts the representativeness heuristic. Cognitive Development, 6(2), 195–217. https://doi.org/10.1016/0885-2014(91)90036-D
2.
AlaybekB.WangY.DalalR. S.DubrowS.BoemermanL. S. (2022). The relations of reflective and intuitive thinking styles with task performance: A meta-analysis. Personnel Psychology, 75(2), 295–319. https://doi.org/10.1111/peps.12443
3.
AuN.FeldmanG. (2020). Revisiting “goals as reference points”: Replication and extensions of Heath et al. (1999). https://doi.org/10.17605/OSF.IO/WMQTB
4.
BakkenB. T.HanssonM.HæremT. (2024). Challenging the doctrine of “non-discerning” decision-making: Investigating the interaction effects of cognitive styles. Journal of Occupational and Organizational Psychology, 97, 209–232. https://doi.org/10.1111/joop.12467
BatesD.MächlerM.BolkerB.WalkerS. (2014). Fitting linear mixed-effects models using lme4. ArXiv:1406.5823. http://arxiv.org/abs/1406.5823
7.
BrannonL. A.CarsonK. L. (2003). The representativeness heuristic: Influence on nurses’ decision making. Applied Nursing Research, 16(3), 201–204. https://doi.org/10.1016/S0897-1897(03)00043-0
8.
BusenitzL. W.BarneyJ. B. (1997). Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making. Journal of Business Venturing, 12(1), 9–30. https://doi.org/10.1016/S0883-9026(96)00003-1
9.
CeschiA.CostantiniA.SartoriR.WellerJ.Di FabioA. (2019). Dimensions of decision-making: An evidence-based classification of heuristics and biases. Personality and Individual Differences, 146, 188–200. https://doi-org.ezproxy.library.bi.no/10.1016/j.paid.2018.07.033
10.
ChanH. C.FeldmanG. (2024). Representativeness heuristic in intuitive predictions: Replication Registered Report of problems reviewed in Kahneman and Tversky (1973). https://doi.org/10.17605/OSF.IO/8ZHCJ
11.
ChandrashekarS.ChengY. H.FongC. L.LeungY. C.WongY. T.ChengB. L.FeldmanG. (2021). Frequency estimation and semantic ambiguity do not eliminate conjunction bias, when it occurs: Replication and extension of Mellers, Hertwig, and Kahneman (2001). Meta-Psychology, 5. https://doi.org/10.15626/MP.2020.2474
CoxC.MouwJ. T. (1992). Disruption of the representativeness heuristic: Can we be perturbed into using correct probabilistic reasoning?Educational Studies in Mathematics, 23(2), 163–178. https://doi.org/10.1007/BF00588054
14.
EpsteinS. (1998). Cognitive-experiential self-theory. In BaroneD. F.HersenM.Van HasseltV. B. (Eds.), Advanced personality. The Plenum series in social/clinical psychology (pp. 211–238). Springer. https://doi.org/10.1007/978-1-4419-8580-4_9
FusterA.LaibsonD.MendelB. (2010). Natural expectations and macroeconomic fluctuations. Journal of Economic Perspectives, 24(4), 67–84. https://doi.org/10.1257/jep.24.4.67
17.
GalavottiI.LippiA.CerratoD. (2021). The representativeness heuristic at work in decision-making: Building blocks and individual-level cognitive and behavioral factors. Management Decision, 59(7), 1664–1683. https://doi.org/10.1108/MD-10-2019-1464
18.
GigerenzerG. (1996). On narrow norms and vague heuristics: A reply to Kahneman and Tversky. Psychological Review, 103(3), 592–596. https://doi.org/10.1037/0033-295X.103.3.592
19.
GretherD. M. (1992). Testing Bayes rule and the representativeness heuristic: Some experimental evidence. Journal of Economic Behavior & Organization, 17(1), 31–57. https://doi.org/10.1016/0167-2681(92)90078-P
20.
GualtieriS.DenisonS. (2018). The development of the representativeness heuristic in young children. Journal of Experimental Child Psychology, 174, 60–76. https://doi.org/10.1016/j.jecp.2018.05.006
21.
HamiltonK.ShihS. I.MohammedS. (2016). The development and validation of the rational and intuitive decision styles scale. Journal of Personality Assessment, 98(5), 523–535. https://doi.org/10.1080/00223891.2015.1132426
HodgkinsonG. P.ClarkeI. (2007). Conceptual note: Exploring the cognitive significance of organizational strategizing: A dual-process framework and research agenda. Human Relations, 60(1), 243–255. https://doi.org/10.1177/0018726707075297
HodgkinsonG. P.Sadler-SmithE.BurkeL. A.ClaxtonG.SparrowP. R. (2009). Intuition in organizations: Implications for strategic management. Long Range Planning, 42(3), 277–297. https://doi.org/10.1016/j.lrp.2009.05.003
26.
HongC.FeldmanG. (2023). Revisiting the “belief in the law of small numbers”: Conceptual replication and extensions Registered Report of problems reviewed in Tversky and Kahneman (1971) [Stage 1: In-principle acceptance from Peer Community in Registered Report]. https://doi.org/10.17605/OSF.IO/MNS7J
27.
JanéM.XiaoQ.YeungS.*Ben-ShacharM. S.*CaldwellA.*CousineauD.*DunleavyD. J.*ElsherifM.*JohnsonB.*MoreauD.*RiesthuisP.*RöselerL.*SteeleJ.*VieiraF.*ZloteanuM.FeldmanG. (2024). Guide to Effect Sizes and Confidence Intervals. http://dx.doi.org/10.17605/OSF.IO/D8C4G
28.
KahnemanD. (2002, December). Maps of bounded rationality: A perspective on intuitive judgment and choice. In The Sveriges Riksbank Prize in economic sciences in memory of Alfred Nobel (pp. 449–489). https://doi.org/10.1037/0003-066X.58.9.697
29.
KahnemanD.FrederickS. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In GilovichT.GriffinD.KahnemanD. (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49–81). Cambridge University Press. https://doi.org/10.1017/CBO9780511808098.004
KerenG.TeigenK. H. (2004). Yet another look at the heuristics and biases approach. In KoehlerD.HarveyN. (Eds.), Blackwell handbook of judgment and decision making (pp. 89–109). John Wiley.
33.
LakensD. (2017). Equivalence tests: A practical primer for t tests, correlations, and meta-analyses. Social Psychological and Personality Science, 8(4), 355–362. https://doi.org/10.1177/1948550617697177
34.
LakensD.CaldwellA. R. (2021). Simulation-based power analysis for factorial analysis of variance designs. Advances in Methods and Practices in Psychological Science, 4(1), 251524592095150. https://doi.org/10.1177/2515245920951503
35.
LeBelE. P.McCarthyR. J.EarpB. D.ElsonM.VanpaemelW. (2018). A unified framework to quantify the credibility of scientific findings. Advances in Methods and Practices in Psychological Science, 1, 389–402. https://doi.org/10.1177/2515245918787489
36.
LeBelE. P.VanpaemelW.CheungI.CampbellL. (2019). A brief guide to evaluate replications. Meta-Psychology, 3, 1–9. https://doi.org/10.15626/MP.2018.843
37.
LeeM. D.WagenmakersE.-J. (2005). Bayesian statistical inference in psychology: Comment on Trafimow (2003). Psychological Review, 112(3), 662–668. https://doi.org/10.1037/0033-295X.112.3.662
38.
LeeM. D.WagenmakersE. J. (2014). Bayesian cognitive modeling: A practical course. Cambridge university press.
LiM. Y.FeldmanG. (2022). Revisiting mental accounting classic paradigms: Replication of the problems reviewed in Thaler (1999) [Stage 1 In-principle acceptance from Peer Community in Registered Report. Stage 2 preprint]. https://doi.org/10.17605/OSF.IO/V7FBJ
41.
LitmanL.RobinsonJ.AbberbockT. (2017). TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods, 49(2), 433–442. https://doi.org/10.3758/s13428-016-0727-z
42.
McCrayG. E.PurvisR. L.McCrayC. G. (2002). Project management under uncertainty: The impact of heuristics and biases. Project Management Journal, 33(1), 49–57. https://doi.org/10.1177/875697280203300108
NorrisP.EpsteinS. (2011). An experiential thinking style: Its facets and relations with objective and subjective criterion measures. Journal of Personality, 79(5), 1043–1080. https://doi.org/10.1111/j.1467-6494.2011.00718.x
45.
NosekB. A.HardwickeT. E.MoshontzH.AllardA.CorkerK. S.DreberA.VazireS. (2022). Replicability, robustness, and reproducibility in psychological science. Annual Review of Psychology, 73, 719–748. https://doi.org/10.1146/annurev-psych-020821-114157
46.
OlsonC. L. (1976). Some apparent violations of the representativeness heuristic in human judgment. Journal of Experimental Psychology: Human Perception and Performance, 2(4), 599–608. https://psycnet.apa.org/doi/10.1037/0096-1523.2.4.599
47.
ParsonsS.KruijtA. W.FoxE. (2019). Psychological science needs a standard practice of reporting the reliability of cognitive-behavioral measurements. Advances in Methods and Practices in Psychological Science, 2(4), 378–395.
48.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
49.
RevelleW. (2024). psych: Procedures for psychological, psychometric, and personality research (Version 2.3.12) [Software]. Northwestern University. https://CRAN.R-project.org/package=psych
50.
RöselerL.WeberL.StichE.HelgerthK.GüntherM.WagnerF.-S.SchützA. (2022). Measurements of susceptibility to anchoring are unreliable: Meta-analytic evidence from more than 50,000 anchored estimates. https://doi.org/10.31234/osf.io/b6t35
51.
ShilohS.SaltonE.SharabiD. (2002). Individual differences in rational and intuitive thinking styles as predictors of heuristic responses and framing effects. Personality and Individual Differences, 32(3), 415–429. https://doi.org/10.1016/S0191-8869(01)00034-4
52.
SimonsohnU. (2015). Small telescopes: Detectability and the evaluation of replication results. Psychological science, 26(5), 559–569. https://doi.org/10.1177/0956797614567341
StolwijkS.VisB. (2021). Politicians, the representativeness heuristic and decision-making biases. Political Behavior, 43(4), 1411–1432. https://doi.org/10.1007/s11109-020-09594-6
56.
SundaliJ.CrosonR. (2006). Biases in casino betting: The hot hand and the gambler’s fallacy. Judgment and Decision Making, 1(1), 1–12. http://doi.org/10.1017/S1930297500000309
ThalerR. H. (1999). Mental accounting matters. Journal of Behavioral decision making, 12(3), 183–206. (https://doi.org/10.1002/(SICI)1099-0771(199909)12:3%3C183::AID-BDM318%3E3.0.CO;2-F
59.
ThalerR. H. (2016). Behavioral economics: Past, present, and future. American Economic Review, 106(7), 1577–1600. https://doi.org/10.1257/aer.106.7.1577
60.
TverskyA.KahnemanD. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110. https://doi.org/10.1037/h0031322
TverskyA.KahnemanD. (1974). Judgment under uncertainty: Heuristics and biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185(4157), 1124–1131.
63.
TverskyA.KahnemanD. (1982). Judgments of and by representativeness. In KahnemanD.SlovicP.TverskyA. (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 84–98). Cambridge University Press.
WhelehanD. F.ConlonK. C.RidgwayP. F. (2020). Medicine and heuristics: Cognitive biases and medical decision-making. Irish Journal of Medical Science, 189, 1477–1484. https://doi.org/10.1007/s11845-020-02235-1
66.
WickhamH. (2016). ggplot2: Elegant graphics for data analysis (Version 3.4.4). Springer. https://ggplot2.tidyverse.org
67.
WickhamH.AverickM.BryanJ.ChangW.McGowanL. D. A.FrançoisR.YutaniH. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
68.
WickhamH.MillerE.SmithD. (2023). haven: Import and export “SPSS,” “Stata” and “SAS” files (Version 2.0.0) [Software]. https://github.com/tidyverse/haven
ZhuH. (2021). kableExtra: Construct complex table with “Kable” and pipe syntax (Version 1.3.4.9). https://rdrr.io/cran/kableExtra/
71.
ZwaanR. A.EtzA.LucasR. E.DonnellanM. B. (2018). Making replication mainstream. Behavioral and Brain Sciences, 41, Article e120. https://doi.org/10.1017/S0140525X17001972
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
