Between ignorance and truth: Partition dependence and learning in judgment under uncertainty.

In 3 studies, participants viewed sequences of multiattribute objects (e.g., colored shapes) appearing with varying frequencies and judged the likelihood of the attributes of those objects. Judged probabilities reflected a compromise between (a) the frequency with which each attribute appeared and (b) the ignorance prior probability cued by the number of distinct values that the focal attribute could take on. Thus, judged probabilities were partition dependent, varying with the number of events into which the state space was subjectively divided. This bias was diminished among participants more confident in what they learned, was strong and insensitive to level of confidence when ignorance priors were especially salient, and required ignorance priors to be salient only when probabilities were elicited (not during encoding).

[1]  F. Attneave Psychological probability as a function of experienced frequency. , 1953, Journal of experimental psychology.

[2]  D. Erlick,et al.  ABSOLUTE JUDGMENTS OF DISCRETE QUANTITIES RANDOMLY DISTRIBUTED OVER TIME. , 1964, Journal of experimental psychology.

[3]  W. T. Singleton,et al.  Man-machine systems , 1974 .

[4]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[5]  Lynn Hasher,et al.  Automatic encoding of category size information. , 1980 .

[6]  B. Fischhoff,et al.  Journal of Experimental Psychology: Human Learning and Memory , 1980 .

[7]  N. Anderson Foundations of information integration theory , 1981 .

[8]  L Hasher,et al.  Automatic processing of fundamental information: the case of frequency of occurrence. , 1984, The American psychologist.

[9]  J. G. Hollands,et al.  Engineering Psychology and Human Performance , 1984 .

[10]  L. Barsalou,et al.  The roles of automatic and strategic processing in sensitivity to superordinate and property frequency , 1986 .

[11]  A Parducci,et al.  The category effect with rating scales: number of categories, number of stimuli, and method of presentation. , 1986, Journal of experimental psychology. Human perception and performance.

[12]  J. Jonides,et al.  On the automaticity of frequency coding: effects of competing task load, encoding strategy, and intention , 1986 .

[13]  R. Hastie,et al.  The relationship between memory and judgment depends on whether the judgment task is memory-based or on-line , 1986 .

[14]  G. Northcraft,et al.  Experts, amateurs, and real estate: An anchoring-and-adjustment perspective on property pricing decisions , 1987 .

[15]  A. Tversky,et al.  Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment , 1983 .

[16]  William F. Wright,et al.  Effects of situation familiarity and financial incentives on use of the anchoring and adjustment heuristic for probability assessment , 1989 .

[17]  M. Peterson,et al.  Frequency judgements: the problem of defining a perceptual event. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[18]  J. S. Freund,et al.  Judgments of Category Size: Now You Have Them, Now You Don't , 1989 .

[19]  M H Birnbaum,et al.  Judgments of proportions. , 1990, Journal of experimental psychology. Human perception and performance.

[20]  Scot Burton,et al.  TASK CONDITIONS, RESPONSE FORMULATION PROCESSES, AND RESPONSE ACCURACY FOR BEHAVIORAL FREQUENCY QUESTIONS IN SURVEYS , 1991 .

[21]  G. Gigerenzer How to Make Cognitive Illusions Disappear: Beyond “Heuristics and Biases” , 1991 .

[22]  C. Wickens Engineering psychology and human performance, 2nd ed. , 1992 .

[23]  N. Sanders,et al.  Journal of behavioral decision making: "The need for contextual and technical knowledge in judgmental forecasting", 5 (1992) 39-52 , 1992 .

[24]  K. Fiedler,et al.  Two halfs may be more than one whole : category-split effects on frequency illusions , 1994 .

[25]  A. Tversky,et al.  Support theory: A nonextensional representation of subjective probability. , 1994 .

[26]  G. Gigerenzer On Narrow Norms and Vague Heuristics: A Reply to Kahneman and Tversky (1996) , 1996 .

[27]  Derek J. Koehler,et al.  Organizational Behavior and Human Decision Processes a Strength Model of Probability Judgments for Tournaments Plished by Estimating Two Strength Values for Each , 2022 .

[28]  D Kahneman,et al.  On the reality of cognitive illusions. , 1996, Psychological review.

[29]  A. Tversky,et al.  Heuristics and Biases: Unpacking, Repacking, and Anchoring: Advances in Support Theory , 2002 .

[30]  F. Conrad,et al.  Strategies for estimating behavioural frequency in survey interviews. , 1998, Memory.

[31]  Gary L. Brase,et al.  Individuation , Counting , and Statistical Inference : The Role of Frequency and Whole-Object Representations in Judgment Under Uncertainty , 1998 .

[32]  A. Tversky,et al.  A Belief-Based Account of Decision Under Uncertainty , 1998 .

[33]  Maria Sonino Legrenzi,et al.  Naive probability: a mental model theory of extensional reasoning. , 1999, Psychological review.

[34]  C. Fox Strength of Evidence, Judged Probability, and Choice Under Uncertainty , 1999, Cognitive Psychology.

[35]  C. Gettys,et al.  MINERVA-DM: A memory processes model for judgments of likelihood. , 1999 .

[36]  D. Koehler,et al.  Probability judgment in three-category classification learning. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[37]  Brian P. Dyre,et al.  Bias in proportion judgments: the cyclical power model. , 2000, Psychological review.

[38]  N. Epley,et al.  Putting Adjustment Back in the Anchoring and Adjustment Heuristic: Differential Processing of Self-Generated and Experimenter-Provided Anchors , 2001, Psychological science.

[39]  M. Young,et al.  Likelihood judgment based on previously observed outcomes: the alternative-outcomes effect in a learning paradigm , 2002, Memory & cognition.

[40]  D. Kahneman,et al.  Heuristics and Biases: The Psychology of Intuitive Judgment , 2002 .

[41]  Craig R. Fox,et al.  Partition Priming in Judgment Under Uncertainty , 2003, Psychological science.

[42]  M. Dougherty,et al.  Probability judgment and subadditivity: The role of working memory capacity and constraining retrieval , 2003, Memory & cognition.

[43]  F. Conrad,et al.  Estimating the frequency of events from unnatural categories , 2003, Memory & cognition.

[44]  Jonathan Levav,et al.  Partition-edit-count: naive extensional reasoning in judgment of conditional probability. , 2004, Journal of experimental psychology. General.

[45]  N. Epley,et al.  When effortful thinking influences judgmental anchoring: differential effects of forewarning and incentives on self‐generated and externally provided anchors , 2005 .

[46]  Robert T. Clemen,et al.  Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior , 2005, Manag. Sci..

[47]  F. Strack,et al.  Playing Dice With Criminal Sentences: The Influence of Irrelevant Anchors on Experts’ Judicial Decision Making , 2006, Personality & social psychology bulletin.

[48]  Michael R. Dougherty,et al.  Differences between probability and frequency judgments: The role of individual differences in working memory capacity☆ , 2006 .

[49]  George R. S. Weir,et al.  ON MAN-MACHINE SYSTEMS , 2007 .

[50]  Robert T. Clemen,et al.  Interior Additivity and Subjective Probability Assessment of Continuous Variables , 2008, Manag. Sci..