两种概率表征的贝叶斯推理的加工过程
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
贝叶斯推理是概率推理的重要组成部分,基础率忽视、框架效应现象一直是该领域研究的重要课题。尽管人们在概率表征形式、概率表征的信息特征、问题的呈现方式对贝叶斯推理的影响方面做了大量的研究,但还缺乏一个整合的理论模型。本研究在推理的双重加工理论和生态理性的视野下来揭示贝叶斯推理的认知加工特点和现实适应性。该研究对揭示人们在不确定性情况下进行推理、判断和决策的认知心理规律具有重要的理论意义和现实意义。
     本研究有四个实验,1)系统地考察了概率信息的表征形式对贝叶斯推理的影响,2)利用现实的、标准的贝叶斯问题探讨了不同概率表征的贝叶斯推理题的试题结构的同质性,3)在不同的推理策略下,分析了基础率水平对百分比、自然频次表征的贝叶斯后验概率值的推算的影响,4)从事件性质、主体相关性、事件的重要程度三个因素来揭示贝叶斯推理的框架效应的本质。该研究提出了“推理的试题和知识双重加工的扩展模型”。
     本研究获得了以下主要结论:
     1)概率词表征的贝叶斯推算实质是判断过程。
     2)贝叶斯判断的正确率高于贝叶斯推算,判断过程并不是经由贝叶斯推算得出概率,再做出判断。
     3)在实验一中,三种概率表征(百分比、自然频次、概率词)下,自然频次表征更适合于被试正确完成贝叶斯推理,但存在学科背景的差异,说明其优越性并不是进化的结果。
     4)贝叶斯推理的策略分为规则(正确规则、错误规则)、内容(命题知识、概率简捷式)和直觉;个人意愿对整个推理过程会有一定程度的影响。
     5)不同概率表征的贝叶斯推理结论正确的差异性源于试题结构与推理者知识结构匹配的吻合程度,与概率的表征形式无关。
     6)基础率并未得到忽视。
     7)贝叶斯推理的框架效应本质上是个人意愿的效果。
Bayesian reasoning is an important part of probability reasoning, base-rate neglect and framing effects are always of great importance in this reseach. However, people have done a lot of work on the influence of probability representation, information structure and question form on Bayesian inference, but an integrated theoretical has not been obtained. In the sight of dual-process theories of reasoning and ecological rationality, this study tries to explore cognitive rule of Bayesian reasoning and adaptive strategies. This study is important for exploring cognitive rule of reasoning, judgment, decision making under uncertain condition.
     There are four experiments in the study,1) effects of probability representation on Bayesian reasoning, 2) homogeneities of construct of items between realistic, normal Bayesian problem , 3) influence of base rate on Bayesian inference, 4) framing effect on Bayesian reasoning. This study concludes The Expanded Model of Item and Knowledge.
     The main findings of this study are as follows:
     1) Process of verbal probability format on Bayesian reasoning is process of judgment.
     2) Results of Bayesian judgement are better than those of calculation.
     3) Frequency format is better than other format, but there are differences among participants of different subject.
     4) Strategies of Bayesian reasoning include right rule, error rule, proposition, probability heuristics and intuition. Desire impact on process of reasoning.
     5) It is the structure of item, not probability format, causes the difference of results of posterior probability.
     6) Base-rate neglect does not exist.
     7) Framing effect really is from the influence of personal desire.
引文
Arkes. H. R. (1991). Cost and benefits of judgment errors: implications for debiasing. Psychological Bulletin, 110: 486-498.
    Arrow, K. J. (1982). Risk perception in psychology and economics. Economic Inquiry, 20: 1-9.
    Beyth-Marom, R. (1982). How probable is probable? A numerical translation of verbal probability expressions. Journal of Forecasting, 1: 257-269.
    Cheng, P. W. and Holyoak, K. J. (1985). Pragmatic reasoning schemas. Cognitive Psychology, 17: 391-416.
    Cherniak,C. (1986). Minimal rationality. Cambridge, MA: MIT Press.
    Clarke, V. A., Ruffin, C., Hill, D. L. & Beamen, A. L. (1992). Ratings of orally presented verbal expressions of probability by a heterogeneous sample. Journal of Applied Social Psychology, 22: 638-656.
    Cohen, L. J. (1981). Can human irrationality be experimentally demonstrated? Behavioral and Brain Science, 4: 317-370.
    Cosmides,L., & Tooby, J.(1996). Are humans good intuitive statiscians after all? Rethinkingsome conclusions from the literature on judgment under uncertainty. Cognition, 58:1-73.
    Dehaene, S. (1992). Varieties of numerical abilities. Cognitive, 44:1-42.
    Dehaene, S., Spelke, E., Pinel, P., Stanescu, R. & Tsivkin, S. (1999). Source of mathematical thinking : Behavioral and brain– imaging evidence[J]. Science, 284:970-974.
    Deloche,G., & Seron, X. (1982). From one to 1: An analysis of a transcoding procrss by means of neuropsychological data. Cognition, 12:119-149.
    Denes-Raj, V. & Epstein, S. (1994). Conflict between intuitive and rational processing: When people behave against their better judgment. Journal of Personality and Social Psychology, 66: 819-829.
    Eddy, D. M., (1982). Probabilistic reasoning in clinical medicine: Problem and opportunities. In D. Kahneman, P.Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases. Cambridge, England: Cambridge University Press, 249-267.
    Epstein, S., Donovan, S., & Denes-Raj, V. (1999). The missing link in the paradox of the Linda conjunction problem: Beyond knowing and thinking of the conjunction rule, the intrinsic appeal of heuristic processing. Personality and Social Psychology Bulletin, 25: 204-214.
    Edwards, W. (1968). Conserbatism in human information processing.In B.Kleinmuntz ( Ed.),Formal representation of human judgment . New York:Wiley, 17-52.
    Edwards, W. (1961). Behavioral decision theory. Annual Review of Psychology, 12:473-498.
    Fiedler, K., Brinkmann, B., Betsch, T., & Wild, B. (2000). A sampling approach to biases in conditional probability judgments: beyond base rate neglect and statistical formal. Journal of Experimental Psychology: General, 129: 399-418.
    Evans, J. S. B. T., & Over, D. E.(1996). Rationality and Reasoning. East Sussex. UK, Psychology press.
    Evans, J. S. B. T., Handley, S. J., Perham, N., Over, D. E., & Thompson, V. A.(2000). Frequency versus probability formats in statistical wors problems. Cognition, 77: 197-213.
    Evans, J. S. B. T., Curtis-Holmes, J. (2005). Rapid responding increases belief bias: Evidence for the dual-process theory of reasoning. Thinking & Reasoning, 11(4):382-389.
    Frederick, S. W., & Fischhoff, B. (1998). Scope (in) sensitivity in elicited valuations. Risk, Decision, and Policy, 3: 109-123.
    Gigerenzer, G.., & Goldstein, D. G.. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103:650-669.
    Gigerenzer, G.., Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review , 102: 684-704.
    Gigerenzer, G.. (1996). On narrow norms and vague heuristics: A reply to Kahneman and Tversky(1996). Psychological Review, 103: 592-596.
    Gigerenzer, G.. (1991). How to make cognition illusions disappear: Beyond“heuristics and biases.”In W. Stroebe & M. Hewstone(Eds.), European Review of Social Psychology, 2:83-115.
    Gigerenzer, G.. (1993). The bounded rationality of probabilistic mental models. In K.J. Manktelow & D.E. Over (Eds.), Rationality: Psychological and philosophical perspectives (283-313). London: Routledge.
    Gigerenzer, G.. (1991). From tools to theories: A heuristic of discovery in cognitive psychology. Psychological Review, 98:254-267.
    Gigerenzer, G., Hoffrage , U., & Ebert, A. (1998). AIDS counseling for low-risk clients. Aids Care, 10:197-211.
    Gigerenzer, G., Todd, P. M., & the ABC Reasearch Group. (1999a). Simple heuristics that make us smart, New York: Oxford University Press.
    Gigerenzer, G., & Hoffrage, U. (1999b). Helping people overcome difficulties in Bayesian reasoning: a reply to Lewis and Keren (1999) and Mellers and McGraw (1999). Psychological Review, 106:425-430.
    Gilbert, D. T(.2002). Inferential correction. In T.Gilovich,D. Griffin, & D.Kahneman (Eds.) , Heuristics and biases (167-184). New York: Cambridge University Press.
    Girotto, V., & Gonzalez, M. (2001). Solving probabilistic and statistical problems: a matter ofnformation structure and question form .Cognition, 78:247-276.
    Glymour, C.N. (1992). Think Through: An Introduction to Philosophical Issue and Achievements. Cambridge, MA: MIT Press.
    Goldman, A. I. (1978). Epistemics: The regulative theory of cognition. Journal of Philosophy, 55:509-523.
    Groner, M., Groner, R., & Bischof, W. F. (1983). Approaches to heuristics: A historical review. In R. Groner(Ed.), Methods of heuristics (1-18). Hillsdale, NJ:Erlbaum.
    Harman, G.. (1995). Rationality. In Thinking(vol.3,175-211).E. E. Smith & D. N. Osherson(Eds.). Cambridge, MA:MIT Press.
    Hardman, D. ,Macchi, L., (2003). Thinking :psychological perspectives on reasoning , judgment and decision making,John Wiley & Sons Ltd.
    Hoffrage, U., Gigerenzer, G.., Krauss.,S., & Martignon, L. (2002). Representation facilitates reasoning: what natural frequencies are and what they are not. Cognition, 78: 247-276.
    Hsee, C. K. (1996). The evaluability hypothesis: An explanation for preference reversals between joint and separate evaluations of alternatives. Organizational Behavior and Human Decision Processes, 67: 242-257.
    Hsee, C. K. (1998). Less is better: when low-value options are valued more highly than high-value options. Journal of Behavioral Decision Making, 11: 107-121.
    Jaffe-Katz, A., Budescu, D. V. , & Wallsten, T. S. (1989). Timed magnitude comparisons of numerical and nonnumerical expressions of uncertainty. Memory & Cognition , 17:249-264.
    Johnson-Laird, P. N., Legrenzi, P., Girotto, V., Legrenzi, M. S., Caverni, J. P. (1999). Naive probability: A mental model theory of extensional reasoning. Psychological Review, 106: 62-88.
    Johnson-Laird, P. N., Legrenzi, P., Girotto, V., Legrenzi, M. S. (2003). Possibilities and probabilities.In Hardman,D. ,Macchi,L.,. Thinking :psychological perspectives on reasoning , judgment and decision making,John Wiley & Sons Ltd, 147-165.
    Kaheman, D.,& Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive Psychology, 3: 430-454.
    Kaheman, D. (2003). A perspective on judgment and choice. American Psychologist, 58(9): 697-720.
    Kareev, Y. (1995a). Through a narrow window-working memory capacity and the detection of covariation. Cognition, 56: 263-269.
    Kareev, Y. (1995b). Positive bias in the perception of covariation. Psychological Review, 102: 490-502.
    Kareev, Y. (2000). Seven ( indeed, plus or minus two) and detection of correlations. Psychological Review, 107: 397-402.
    Kareev, Y., Lieberman, I. & Lev, M. (1997). Through a narrow window: Sample size and theperception of correlation. Journal of Experimental Psychology: General, 126: 278-287.
    Kelley,H.H. (1967). Attribution theory in social psychology.In D.Levine(ED.),Nebraska Symposium on Motivation(Vol.15).Lincoln:University of Nebraska Press.
    Klaczynski, P. A., Daniel, D. B. (2005). Individual differences in conditional reasoning: A dual-process account. Thinking & Reasoning, 11(4): 305-325.
    Koehler, D. J. (1996). A strength model of probability judgments for tournaments. Organizational Behavior and Human Decision Processes, 66: 16-21.
    LeBoeuf,R.A,.& Shafir,E. (2003).Deep thoughts and shallow frames:On the susceptibility to framing effects.Journal of behavioral Decision Making, 16:77-92
    Lehman, D. R., Lempert, R. O., & Nisbett, R. E. (1988). The effects of graduate training on reasoning: Formal discipline and thinking about everyday-life events. American Psychologist, 43: 431-442.
    Lewis,C., & Keren,G. (1999). On the difficulties Underlying Bayesian Reasoning: Acomment on Gigerenzer and Hoffrage. Psychological Review, 106:411-416.
    Lichtenstein, S. & Newman, J. R. (1967). Empirical scaling of common verbal phrases associated with numerical probabilities. Psychonomic Science, 9:563-564.
    Luce, R. D., Raiffa, H. (1957). Games and Decisions. New York: Wiley. Macchi, L., & Mosconi, G. (1998). Computational features vs frequentist phrasing in the base-rate fallacy. Swiss Journal of Psychology, 57: 79-85.
    Manktelow, K.(1999). Reasoning and Thinking .UK . Psychology Press , 165-189.
    McCloskey, M. (1992). Cognitive mechanisms in numerical processing : Evidence from acquired dyscalculia.Cognition, 44: 107-157.
    McCloskey, M., Caramazza, A., & Basili, A. (1985). Cognitive mechanisms in number processing and calculation :Evidence from dyscalculia . Brain and Cognition, 4: 171-196.
    Mellers, B., & McGraw, P. (1999). How to Improve Bayesian Reasoning : Comment on Gigerenzer and Hoffrage (1995). Psyhological Review, 106:417-427.
    McNeil, B. J., Pauker, S. G., Sox, H. C. ,& Tversky, A. (1982). On the elicitation of preferences for alternative therapies. New England Journal of Medicine, 306:1259-1262.
    Renooij, S., Witteman, C. (1999). Talking probabilities: communicating probabilistic information with words and numbers. International Journal of Approximate Reasoning, 22: 169-194.
    Ross, S. M. (1997). A First Course in Probability. Upper Saddle River, NJ: Prentice Hall. 5th ed.
    Oaksford, M., Chater, N. and Larkin, J. (2000). Probability and polarity biases in conditional inference. Journal of Experimental Psychology: LMC, 4: 883-899.
    Oaksford, M., Chater, N. (1999). Probabilistic effects in data selection. Thinking and Reasoning, 5:193-243.
    Oaksford, M., Chater, N. (1993). Reasoning theories and bounded rationality. In Rationality: Psychological and philosophical perspectives (31-60), K. Manktelow & D. Over(Eds.) London: Routledge.
    Oaksford, M., Chater, N. (1995). Theories of reasoning and the computational explanation of everyday inference. Thinking and Reasoning, 1:121-152.
    Oaksford, M., Chater, N. (1998). Rationality in an uncertain world. Hove ,England: Psychology Press.
    Payne, J. W., Bettman, J. R. & Johnson, E. J. (1993). The Adaptive Decision Maker. New York: Cambridge University Press.
    Phillips,L. D., Edwards,W. (1966) Sampling distribution and probability revision. Journal of Experimental Psychology, 76: 236-243.
    Renooij, S. & Witteman, C. (1999). Talking probabilities : communicating probabilistic information with words and numbers. International Journal of Approximate Reasoning, 22:169-194.
    Roberts, M. J., & Newton, E. J. (2002) Inspection times, the change task, and the rapid-response selection task. Quarterly Journal of Experimental Psychology, 54A:1031-1048.
    Rouanet, H. (1961).êtudes de decisions expérimentales et calcul de probabilities.[Studies of experimental decision making and probability calculus] In Colloques internationaux du centre national de la recherchéscientifique(33-43). Paris:êditions du Centre National de la Recherche Scientifique.
    Shair, E. (1993). Choosing versus rejecting: Why some options are both better and worse than others. Memory and Cognition, 21:546-556.
    Simon, H. A., (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69:99-118.
    Smith, S. M., Levin, I. P. (1996). Need for cognition and choice framing effects. Journal of Behavioral Decision Making, 9: 283-290.
    Sloman,S.A. (1996a). The empirical case for two systems of reasoning. Psychological Bulletin, 119. 3-22.
    Sloman,S.A. (1996b).The probative value of simultaneous contradictory belief: Reply to Gigerenzer and Regier (1996). Psychological Bulletin, 119:27-30.
    Sloman, S. A. Over, D., Slovak, L. et al. (2003). Frequency illusion and other fallacies. Organizational Behavior and Human Decision Processes, 91: 296-309.
    Sloman, S. A. (2002). The empirical case for two systems of reasoning, In Heuristics and Biases: The Psychology of Intuitive Judgment (Gilovich,T.et al.,eds), Cambridge University Press, 379-397.
    Slovic, P., Finucane, M., Peters, E., MacGregor, D. G.. (2002). The affect heuristic. In Heuristics and Biases: The Psychology of Intuitive Judgment (Gilovich,T.et al.,eds).Cambridge University Press, 397-421.
    Stanovich, K. E., & West, R. F. (1999). Individual differences in reasoning and the heuristics and biases debate, Learning and Individual Difference: American Psychological Association.
    Stanovich, K. E.(2004). The Robot’s Rebellion: Finding Meaning In The Age Of Darwin, Chicago University Press.
    Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate. Behavioral and Brain Science, 23: 645-665.
    Stein, E. (1996). Without good reason: The rationality debate in philosophy and cognitive science. Oxford, U.K: Oxford University Press.
    Stich, S. P.(1990). The fragmentation of reason. Cambridge, Ma: MIT Press.
    Tanner, W. P., Jr., & Swets, J. A. (1954). A decision-making theory of visual detection. Psychological Review, 61:725-731.
    Tavana, M. , Kennedy, D. T. & Mohebbi, B. (1997). An applied study using the analytic hierarchy process to translate common verbal phrases to numerical probabilities. Journal of Behavioral Decision Making, 10:133-150.
    Thaler,R. H. (1991). The psychology of choice and the assumptions of economics. In R. H. Thaler (Ed.), Quasi-rational economics (137-166). New York: Russell Sage Foundation.
    Teigen, K. H., Brun, W. (2003). Verbal expressions of uncertainty and probability. In Hardman,D. ,Macchi,L. Thinking :psychological perspectives on reasoning , judgment and decision making,John Wiley & Sons Ltd. 125-147.
    Tversky,D., & Kahneman, D. (1974). Judgment under uncertainty: heuristics and biases. Science, 185:1124-1131
    Tversky, A. & Kahneman, D.(1980). Causal schemas in judgment under uncertainty. In Progress in social psychology,M.Fishbein(ED).Hillsdale,NJ:Erlbaum.
    Tversky, A. & Kahneman, D.(1986). Rational choice and the framing of decisions. Journal of Business, 59: S251-S278.
    Tversky, A. & Kahneman, D.(1982). Evidential impact of base rates. In D. Kahneman, D, P.Slovic, &A. Tversky (Eds), Judgment under uncertainty: Heuristics and biases, Cambridge, England: Cambridge University Press, 153-160.
    Tversky, A. & Kahneman, D.(1981, January 30). The framing of decisions and the psychology of choice. Science, 211: 453-458.
    Tversky,A., Kahneman ,D. (1981). The framing of decisions and psychology of choice . Science, 211: 453-458.
    Vranas,P. B. M. (2000). Gigerenzer’s normative critique of Kahneman and Tversky. Cognition, 76: 179-193.
    Wallsten ,T. S., Budescu , D. V. , Zwick , R. (1993). Comparing the calibration and coherence of numerical and verbal probability judgment . Management Science , 39:176-190.
    Windschitl,P. D., (2000). The binary additivity of subjective probability does not indicate the binary complementarity of perceived certainty. Organizational Behavior and Human Decision Processes, 81: 195-225.
    Windschitl, P. D., Wells, G.. L., (1996). Measuring psychological uncertainty: verbal versus numeric methods, Journal of experimental psychology:Applied, 2:343-364.
    Windschitl, P. D., Wells, G.. L., (1998). The alternative-outcomes effect. Journal of Personality and Social Psychology, 75: 1411-1423.
    Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35: 151-175.
    Zhu, L., Gigerenzer, G.. (2006) Children can solve Bayesian problems: the role of representation in mental computation. Cognition, 98: 287-308.
    G.Gigerenzer,包燕.生态学智力:人类的推理算法对频率的适应.心理科学进展,2001,9(4):325-329.
    Samuel Kotz,吴喜之.现代贝叶斯统计学,中国统计出版社,2000.
    董奇,张红川,周新林.数学认知:脑与认知科学的研究成果及其教育启示,北京师范大学学报(社会科学版),2005,3: 40-46.
    董奇,张红川.估算能力与精算能力:脑与认知科学的研究成果及其对数学教育的启示. 2002,5: 46-51.
    高定国,肖晓云译.认知心理学.上海:华东师范大学出版社,2004.
    胡竹菁.演绎推理的心理学研究.北京:人民教育出版社,2000 .
    胡竹菁,朱丽萍.人类推理的心理学研究.北京:高等教育出版社,2007 .
    胡竹菁,张厚粲.论三段论推理过程中结论正确性的两种判定标准.心理学报,1996,28:58-63.
    胡竹菁.推理心理学研究中的逻辑加工与非逻辑加工评析.心理科学,2002,25: 318-321.
    胡竹菁.“心理模型”与“知识与试题双重结构模型”的实验比较研究.心理科学,1999,22(4):362-364
    贾乃光译.统计决策论及贝叶斯分析.北京:中国统计出版社,1998.
    邱江,张庆林.有关条件推理中概率效应的实验研究.心理科学,2005,28(3):554-557.
    邱江,张庆林.条件推理与概率判断.心理科学,2007,30(2):301-304.
    史滋福,邱江,张庆林.明确嵌套集合关系对贝叶斯推理的促进效应.心理学报, 2006, 38(6):833-840.
    施俊琦,王星译.决策与判断.北京:人民邮电出版社,2004。
    邵志芳,张路路.小概率事件对因果关系认知的影响.心理科学,2003,26(5):914-转911
    邵志芳.思维心理学.上海:华东师范大学出版社,2001.
    王墨耘,莫雷.归类不确定情景下特征的综合条件概率模型.心理学报,2005,37(4):482-490.
    徐媛.贝叶斯推理完成特点及影响因素.华东师大硕士论文,2003.
    赵晓东,傅小兰.贝叶斯推理的改进方法——以频率格式代替概率格式进行信息表征.心理科学,2002,25(1):96-97.
    张向阳.贝叶斯推理的认知特征及其影响因素的实验研究.华南师大博士论文,2003.
    张向阳,刘鸣.贝叶斯推理研究综述.心理科学进展,2002,10(4):388-394
    张向阳,刘鸣,张积家.主体关联性对贝叶斯推理概率估计得影响.心理科学,2006a,29(4):795-797.
    张向阳,刘鸣,张积家.知识图式对贝叶斯推理的影响.心理学探新,2006,26(1):35-38.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700