A Statistical Guide for the Ethically Perplexed Preamble Introduction
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Conjunction Fallacy' Revisited: How Intelligent Inferences Look Like Reasoning Errors
Journal of Behavioral Decision Making J. Behav. Dec. Making, 12: 275±305 (1999) The `Conjunction Fallacy' Revisited: How Intelligent Inferences Look Like Reasoning Errors RALPH HERTWIG* and GERD GIGERENZER Max Planck Institute for Human Development, Berlin, Germany ABSTRACT Findings in recent research on the `conjunction fallacy' have been taken as evid- ence that our minds are not designed to work by the rules of probability. This conclusion springs from the idea that norms should be content-blind Ð in the present case, the assumption that sound reasoning requires following the con- junction rule of probability theory. But content-blind norms overlook some of the intelligent ways in which humans deal with uncertainty, for instance, when drawing semantic and pragmatic inferences. In a series of studies, we ®rst show that people infer nonmathematical meanings of the polysemous term `probability' in the classic Linda conjunction problem. We then demonstrate that one can design contexts in which people infer mathematical meanings of the term and are therefore more likely to conform to the conjunction rule. Finally, we report evidence that the term `frequency' narrows the spectrum of possible interpreta- tions of `probability' down to its mathematical meanings, and that this fact Ð rather than the presence or absence of `extensional cues' Ð accounts for the low proportion of violations of the conjunction rule when people are asked for frequency judgments. We conclude that a failure to recognize the human capacity for semantic and pragmatic inference can lead rational responses to be misclassi®ed as fallacies. Copyright # 1999 John Wiley & Sons, Ltd. KEY WORDS conjunction fallacy; probabalistic thinking; frequentistic thinking; probability People's apparent failures to reason probabilistically in experimental contexts have raised serious concerns about our ability to reason rationally in real-world environments. -
A Task-Based Taxonomy of Cognitive Biases for Information Visualization
A Task-based Taxonomy of Cognitive Biases for Information Visualization Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, and Pierre Dragicevic Three kinds of limitations The Computer The Display 2 Three kinds of limitations The Computer The Display The Human 3 Three kinds of limitations: humans • Human vision ️ has limitations • Human reasoning 易 has limitations The Human 4 ️Perceptual bias Magnitude estimation 5 ️Perceptual bias Magnitude estimation Color perception 6 易 Cognitive bias Behaviors when humans consistently behave irrationally Pohl’s criteria distilled: • Are predictable and consistent • People are unaware they’re doing them • Are not misunderstandings 7 Ambiguity effect, Anchoring or focalism, Anthropocentric thinking, Anthropomorphism or personification, Attentional bias, Attribute substitution, Automation bias, Availability heuristic, Availability cascade, Backfire effect, Bandwagon effect, Base rate fallacy or Base rate neglect, Belief bias, Ben Franklin effect, Berkson's paradox, Bias blind spot, Choice-supportive bias, Clustering illusion, Compassion fade, Confirmation bias, Congruence bias, Conjunction fallacy, Conservatism (belief revision), Continued influence effect, Contrast effect, Courtesy bias, Curse of knowledge, Declinism, Decoy effect, Default effect, Denomination effect, Disposition effect, Distinction bias, Dread aversion, Dunning–Kruger effect, Duration neglect, Empathy gap, End-of-history illusion, Endowment effect, Exaggerated expectation, Experimenter's or expectation bias, -
Avoiding the Conjunction Fallacy: Who Can Take a Hint?
Avoiding the conjunction fallacy: Who can take a hint? Simon Klein Spring 2017 Master’s thesis, 30 ECTS Master’s programme in Cognitive Science, 120 ECTS Supervisor: Linnea Karlsson Wirebring Acknowledgments: The author would like to thank the participants for enduring the test session with challenging questions and thereby making the study possible, his supervisor Linnea Karlsson Wirebring for invaluable guidance and good questions during the thesis work, and his fiancée Amanda Arnö for much needed mental support during the entire process. 2 AVOIDING THE CONJUNCTION FALLACY: WHO CAN TAKE A HINT? Simon Klein Humans repeatedly commit the so called “conjunction fallacy”, erroneously judging the probability of two events occurring together as higher than the probability of one of the events. Certain hints have been shown to mitigate this tendency. The present thesis investigated the relations between three psychological factors and performance on conjunction tasks after reading such a hint. The factors represent the understanding of probability and statistics (statistical numeracy), the ability to resist intuitive but incorrect conclusions (cognitive reflection), and the willingness to engage in, and enjoyment of, analytical thinking (need-for-cognition). Participants (n = 50) answered 30 short conjunction tasks and three psychological scales. A bimodal response distribution motivated dichotomization of performance scores. Need-for-cognition was significantly, positively correlated with performance, while numeracy and cognitive reflection were not. The results suggest that the willingness to engage in, and enjoyment of, analytical thinking plays an important role for the capacity to avoid the conjunction fallacy after taking a hint. The hint further seems to neutralize differences in performance otherwise predicted by statistical numeracy and cognitive reflection. -
Graphical Techniques in Debiasing: an Exploratory Study
GRAPHICAL TECHNIQUES IN DEBIASING: AN EXPLORATORY STUDY by S. Bhasker Information Systems Department Leonard N. Stern School of Business New York University New York, New York 10006 and A. Kumaraswamy Management Department Leonard N. Stern School of Business New York University New York, NY 10006 October, 1990 Center for Research on Information Systems Information Systems Department Leonard N. Stern School of Business New York University Working Paper Series STERN IS-90-19 Forthcoming in the Proceedings of the 1991 Hawaii International Conference on System Sciences Center for Digital Economy Research Stem School of Business IVorking Paper IS-90-19 Center for Digital Economy Research Stem School of Business IVorking Paper IS-90-19 2 Abstract Base rate and conjunction fallacies are consistent biases that influence decision making involving probability judgments. We develop simple graphical techniques and test their eflcacy in correcting for these biases. Preliminary results suggest that graphical techniques help to overcome these biases and improve decision making. We examine the implications of incorporating these simple techniques in Executive Information Systems. Introduction Today, senior executives operate in highly uncertain environments. They have to collect, process and analyze a deluge of information - most of it ambiguous. But, their limited information acquiring and processing capabilities constrain them in this task [25]. Increasingly, executives rely on executive information/support systems for various purposes like strategic scanning of their business environments, internal monitoring of their businesses, analysis of data available from various internal and external sources, and communications [5,19,32]. However, executive information systems are, at best, support tools. Executives still rely on their mental or cognitive models of their businesses and environments and develop heuristics to simplify decision problems [10,16,25]. -
Assessing School and Teacher Effectiveness Using HLM and TIMSS Data from British Columbia and Ontario
Avoiding Ecological Fallacy: Assessing School and Teacher Effectiveness Using HLM and TIMSS Data from British Columbia and Ontario By Yichun Wei B. Eng. University of Hunan M. Sc. University of Hunan A Thesis submitted to the Faculty of Graduate Studies of The University of Manitoba in partial fulfillment of the requirements of the degree of DOCTOR OF PHILOSOPHY Faculty of Education University of Manitoba Winnipeg, MB. Canada Copyright © 2012 by Yichun Wei ABSTRACT There are two serious methodological problems in the research literature on school effectiveness, the ecological problem in the analysis of aggregate data and the problem of not controlling for important confounding variables. This dissertation corrects these errors by using multilevel modeling procedures, specifically Hierarchical Linear Modeling (HLM), and the Canadian Trends in International Mathematics and Science Study (TIMSS) 2007 data, to evaluate the effect of school variables on the students’ academic achievement when a number of theoretically-relevant student variables have been controlled. In this study, I demonstrate that an aggregate analysis gives the most biased results of the schools’ impact on the students’ academic achievement. I also show that a disaggretate analysis gives better results, but HLM gives the most accurate estimates using this nested data set. Using HLM, I show that the physical resources of schools, which have been evaluated by school principals and classroom teachers, actually have no positive impact on the students’ academic achievement. The results imply that the physical resources are important, but an excessive improvement in the physical conditions of schools is unlikely to improve the students’ achievement. Most of the findings in this study are consistent with the best research literature. -
The Impact Factor Fallacy
bioRxiv preprint doi: https://doi.org/10.1101/108027; this version posted February 20, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Title: 2 The impact factor fallacy 3 Authors: 4 Frieder Michel Paulus 1; Nicole Cruz 2,3; Sören Krach 1 5 Affiliations: 6 1 Department of Psychiatry and Psychotherapy, Social Neuroscience Lab, University of Lübeck, 7 Ratzeburger Allee 160, D-23538 Lübeck, Germany 8 2 Department of Psychological Sciences, Birkbeck, University of London, London, UK 9 3 Laboratoire CHArt, École Pratique des Hautes Études (EPHE), Paris, France 10 Corresponding Authors: 11 Frieder Paulus, phone: ++49-(0)451- 31017527, email: [email protected] 12 Sören Krach, phone: ++49-(0)451-5001717, email: [email protected] 13 Department of Psychiatry and Psychotherapy, Social Neuroscience Lab, University of Lübeck, 14 Ratzeburger Allee 160, D-23538 Lübeck, Germany 15 Author contributions: 16 FMP, NC, and SK wrote the manuscript. 17 Running title: The impact factor fallacy 18 Word count abstract: 135 19 Word count manuscript (including footnotes): 4013 20 Number of tables: 1 21 Number of figures: 0 1 bioRxiv preprint doi: https://doi.org/10.1101/108027; this version posted February 20, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 22 Abstract 23 The use of the journal impact factor (JIF) as a measure for the quality of individual 24 manuscripts and the merits of scientists has faced significant criticism in recent years. -
The Clinical and Ethical Implications of Cognitive Biases
THE CLINICAL AND ETHICAL IMPLICATIONS OF COGNITIVE BIASES Brendan Leier, PhD Clinical Ethicist, University of Alberta Hospital/Stollery Children’s Hospital & Mazankowski Heart Institute & Clinical Assistant Professor Faculty of Medicine and Dentistry & John Dossetor Health Ethics Centre Some games 2 Wason selection task • choose two cards to turn over in order to test the following E4 hypothesis: • If the card has a vowel on one side, it must have an even number on the other side 7K 3 • Most subjects make the error of choosing E & 4 E4 • Traditionally subjects fail to select the cards E & 7 that can both correctly confirm and falsify the hypothesis 7K 4 The Monty Hall Problem Monty asks you to choose between three boxes. One box contains a valuable prize, the other two boxes do not. 5 The Monty Hall Problem Box A Box B Box C 6 The Monty Hall Problem After you choose Box A, Monty reveals Box C as empty, and then asks you if you would like to switch your choice. Of the remaining two Box A and Box B, do you switch your choice? 7 Do you switch from A to B? Box A Box B 8 Should you switch from A to B? Box A Box B 9 Yes, you should you switch from A to B Box A Box B 33% 50% 10 last one A bat and a ball cost $1.10 in total. The bat costs 1 dollar more than the ball. How much does the ball cost? 11 Reasoning and Rationality • Sub-field of epistemology • Looks for normative guidance in acquiring/establishing claims to knowledge or systems of inquiry. -
I Correlative-Based Fallacies
Fallacies In Argument 本文内容均摘自 Wikipedia,由 ode@bdwm 编辑整理,请不要用于商业用途。 为方便阅读,删去了原文的 references,见谅 I Correlative-based fallacies False dilemma The informal fallacy of false dilemma (also called false dichotomy, the either-or fallacy, or bifurcation) involves a situation in which only two alternatives are considered, when in fact there are other options. Closely related are failing to consider a range of options and the tendency to think in extremes, called black-and-white thinking. Strictly speaking, the prefix "di" in "dilemma" means "two". When a list of more than two choices is offered, but there are other choices not mentioned, then the fallacy is called the fallacy of false choice. When a person really does have only two choices, as in the classic short story The Lady or the Tiger, then they are often said to be "on the horns of a dilemma". False dilemma can arise intentionally, when fallacy is used in an attempt to force a choice ("If you are not with us, you are against us.") But the fallacy can arise simply by accidental omission—possibly through a form of wishful thinking or ignorance—rather than by deliberate deception. When two alternatives are presented, they are often, though not always, two extreme points on some spectrum of possibilities. This can lend credence to the larger argument by giving the impression that the options are mutually exclusive, even though they need not be. Furthermore, the options are typically presented as being collectively exhaustive, in which case the fallacy can be overcome, or at least weakened, by considering other possibilities, or perhaps by considering a whole spectrum of possibilities, as in fuzzy logic. -
What Can Ecological Studies Tell Us About Death? Yehuda Neumark
Neumark Israel Journal of Health Policy Research (2017) 6:52 DOI 10.1186/s13584-017-0176-x COMMENTARY Open Access What can ecological studies tell us about death? Yehuda Neumark Abstract: Using an ecological study design, Gordon et al. (Isr J Health Policy Res 6:39, 2017) demonstrate variations in mortality patterns across districts and sub-districts of Israel during 2008–2013. Unlike other epidemiological study designs, the units of analysis in ecological studies are groups of people, often defined geographically, and the exposures and outcomes are aggregated, and often known only at the population-level. The ecologic study has several appealing characteristics (suchasrelianceonpublic-domain anonymous data) alongside a number of important potential limitations including the often mentioned ‘ecological fallacy’.Advantagesand disadvantages of the ecological design are described briefly below. Keywords: Ecological fallacy, Ecological studies, Epidemiology, Mortality, Study design Main text In this journal, Gordon et al. [4] employ an ecological "The aim of epidemiology is to decipher nature with re- design to demonstrate variations in mortality patterns spect to human health and disease, and no one should across districts and sub-districts of Israel during the underestimate the complexities of epidemiological research" five-year period of 2008–2013. Standardized mortality [1]. To achieve this lofty and complex goal, the epide- ratios (SMRs) reveal a 25% excess of kidney disease re- miologic investigative toolbox contains various study lated deaths in the Haifa district, for example, while the methodologies including individual-based experimental risk of death from influenza/pneumonia is 25% lower designs (e.g., randomized controlled trial), individual- there than the national average. -
Probability, Confirmation, and the Conjunction Fallacy
Probability, Confirmation, and the Conjunction Fallacy Vincenzo Crupi* Branden Fitelson† Katya Tentori‡ April, 2007 * Department of Cognitive Sciences and Education and CIMeC (University of Trento) and Cognitive Psychology Laboratory, CNRS (University of Aix-Marseille I). Contact: [email protected]. † Department of Philosophy (University of California, Berkeley). Contact: [email protected]. ‡ Department of Cognitive Sciences and Education and CIMeC (University of Trento). Contact: [email protected]. Probability, Confirmation, and the Conjunction Fallacy Abstract. The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt of providing a satisfactory account of the phenomenon has proven challenging. Here, we elaborate the suggestion (first discussed by Sides et al., 2001) that in standard conjunction problems the fallacious probability judgments experimentally observed are typically guided by sound assessments of confirmation relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal result is a confirmation- theoretic account of the conjuntion fallacy which is proven robust (i.e., not depending on various alternative ways of measuring degrees of confirmation). The proposed analysis is shown distinct from contentions that the conjunction effect is in fact not a fallacy and is compared with major competing explanations of the phenomenon, including earlier references to a confirmation-theoretic account. 2 Acknowledgements. Research supported by PRIN 2005 grant Le dinamiche della conoscenza nella società dell’informazione and by a grant from the SMC/Fondazione Cassa di Risparmio di Trento e Rovereto. Versions of this work have been presented at the Cognitive Psychology Laboratory, CNRS – University of Aix-Marseille I, at the workshop Bayesianism, fundamentally, Center for Philosophy of Science, University of Pittsburgh and at the conference Confirmation, induction and science, London School of Economics. -
1 Embrace Your Cognitive Bias
1 Embrace Your Cognitive Bias http://blog.beaufortes.com/2007/06/embrace-your-co.html Cognitive Biases are distortions in the way humans see things in comparison to the purely logical way that mathematics, economics, and yes even project management would have us look at things. The problem is not that we have them… most of them are wired deep into our brains following millions of years of evolution. The problem is that we don’t know about them, and consequently don’t take them into account when we have to make important decisions. (This area is so important that Daniel Kahneman won a Nobel Prize in 2002 for work tying non-rational decision making, and cognitive bias, to mainstream economics) People don’t behave rationally, they have emotions, they can be inspired, they have cognitive bias! Tying that into how we run projects (project leadership as a compliment to project management) can produce results you wouldn’t believe. You have to know about them to guard against them, or use them (but that’s another article)... So let’s get more specific. After the jump, let me show you a great list of cognitive biases. I’ll bet that there are at least a few that you haven’t heard of before! Decision making and behavioral biases Bandwagon effect — the tendency to do (or believe) things because many other people do (or believe) the same. Related to groupthink, herd behaviour, and manias. Bias blind spot — the tendency not to compensate for one’s own cognitive biases. Choice-supportive bias — the tendency to remember one’s choices as better than they actually were. -
The Emperor's Tattered Suit: the Human Role in Risk Assessment
The Emperor’s Tattered Suit: The Human Role in Risk Assessment and Control Graham Creedy, P.Eng, FCIC, FEIC Process Safety and Loss Management Symposium CSChE 2007 Conference Edmonton, AB October 29, 2007 1 The Human Role in Risk Assessment and Control • Limitations of risk assessment (acute risk assessment for major accident control in the process industries) • Insights from other fields • The human role in risk assessment – As part of the system under study – In conducting the study • Defences 2 Rationale • Many of the incidents used to sensitize site operators about process safety “would not count” in a classical risk assessment, e.g. for land use planning • It used to be that only fatalities counted, though irreversible harm is now also being considered • Even so, the fatalities and/or harm may still not count, depending on the scenario • The likelihood of serious events may be understated 3 Some limitations in conventional risk assessment: consequences • “Unexpected” reaction and environmental effects, e.g. Seveso, Avonmouth • Building explosion on site, e.g. Kinston, Danvers • Building explosion offsite, e.g. Texarkana • Sewer explosion, e.g. Guadalajara • “Unexpected” vapour cloud explosion, e.g. Buncefield • “Unexpected” effects of substances involved, e.g. Tigbao • Projectiles, e.g. Tyendinaga, Kaltech • Concentration of blast, toxics due to surface features • “Unexpected” level of protection or behaviour of those in the affected zone, e.g. Spanish campsite, Piedras Negras • Psychological harm (and related physical harm), e.g. 2EH example 4 Some limitations in conventional risk assessment: frequency • Variability in failure rate due to: – Latent errors in design: • Equipment (Buncefield) • Systems (Tornado) • Procedures (Herald of Free Enterprise) – Execution errors due to normalization of deviance Indicators such as: • Safety culture (Challenger, BP, EPA) • Debt (Kleindorfer) • MBAs among the company’s top managers? (Pfeffer) • How realistic are generic failure rate data? (e.g.