Conditional Probability Communication

Conditional Probability Communication is a formal framework within probability communication that specifies how probabilistic information, conditioned on particular evidence or contexts, is systematically conveyed and interpreted to support accurate reasoning under uncertainty.

8

Publications

1.4K

Citations

21

Authors

17

Institutions

Publications per year

2017–2026

1

Authors

21

  1. GG
    Gerd Gigerenzer

    Max Planck Institute for Human Development, Germany

    2 publications · 695 citations

    2

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  2. SM
    Steven M. Kemp

    University of Illinois Urbana-Champaign, United States

    1 publications · 298 citations

    1

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  3. TS
    Thomas S. Wallsten

    University of North Carolina at Chapel Hill, United States

    1 publications · 298 citations

    1

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  4. TB
    Theresa Büchter

    Ludwig-Maximilians-Universität München, Germany

    1 publications · 19 citations

    1

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  5. RZ
    Rami Zwick

    Pennsylvania State University, United States

    1 publications · 298 citations

    1

    h-index

1–5 of 21

Venues

  1. Mathematics

    1 publications · 19 citations

    1

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  2. 1

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  3. Bulletin of the Psychonomic Society

    1 publications · 298 citations

    1

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  4. Proceedings of the National Academy of Sciences

    PNAS · 1 publications · 51 citations

    1

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  5. 1

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1–5