Abstract
We present empirical evidence that human reasoning follows the rules of probability theory, if information is presented in “natural formats”. Human reasoning has often been evaluated in terms of humans’ ability to deal with probabilities. Yet, in nature we do not observe probabilities, we rather count samples and their subsets. Our concept of Markov frequencies generalizes Gigerenzer and Hoffrage’s “natural frequencies”, which are known to foster insight in Bayesian situations with one cue. Markov frequencies allow to visualize Bayesian inference problems even with an arbitrary number of cues.
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References
Eddy, D.M., 1982, Probabilistic reasoning in clinical medicine: problems and opportunities, in: Judgment under Uncertainty: Heuristics and Biases, D. Kahneman, P. Slovic, and A. Tversky, eds., Cambridge University Press, Cambridge, pp. 249–267).
Gigerenzer, G., and Hoffrage, U., 1995, How to improve Bayesian reasoning without instruction: frequency formats, Psychological Review 102:684–704.
Hell, W., Fiedler, K., and Gigerenzer, G., eds., 1993, Kognitive Täuschungen, Spektrum Akademischer Verlag, Berlin-Oxford.
Kahneman, D, Slovic, P., and Tversky, A., eds., 1982, Judgment under uncertainty: Heuristics and biases, Cambridge University Press, Cambridge.
Kahneman, D., and Tversky, A., 1972, Subjective probability: a judgement of representativeness, Cognitive Psychology 3:430–454.
Kahneman, D., and Tversky, A., 1973, On the psychology of prediction, Psychological review 80:237–251.
Lauritzen, S.L., and Spiegelhalter, D.J., 1988, Local computations with probabilities on graphical structures and their application to expert systems (with discussion), J. Roy. Statist. Soc. Ser. B 50:157–224.
Lewis, C., and Keren, G., 1999, On the difficulties underlying Bayesian reasoning: comment on Gigerenzer and Hoffrage, Psychological Review, in press.
Macchi, L., 1995, Pragmatic aspects of the base-rate fallacy, The Quarterly Journal of Experimental Psychology 48A:188–207.
Macchi, L., and Mosconi, G., 1998, Computational features vs frequentist phrasing in the base-rate fallacy, Swiss Journal of Psychology 57:79–85.
Massaro, D., 1998, Perceiving Talking Faces, MIT Press, Boston.
Meilers, B.A., and McGraw, A.P., 1999, How to improve Bayesian reasoning without instruction: comment on Gigerenzer and Hoffrage, Psychological Review, in press.
Spies, M., 1993, Unsicheres Wissen: Wahrscheinlichkeit, Fuzzy-Logik, neuronale Netze und menschliches Denken, Heidelberg, Spektrum Akademischer Verlag, Berlin-Oxford.
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Krauß, S., Martignon, L., Hoffrage, U. (1999). Simplifying Bayesian Inference: The General Case. In: Magnani, L., Nersessian, N.J., Thagard, P. (eds) Model-Based Reasoning in Scientific Discovery. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4813-3_11
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DOI: https://doi.org/10.1007/978-1-4615-4813-3_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7181-6
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