Related Experiment Video
Updated: Mar 3, 2026

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task
Published on: July 22, 2025
Between a conditional's antecedent and its consequent: Discourse coherence vs. probabilistic relevance.
Karolina Krzyżanowska1, Peter J Collins2, Ulrike Hahn2
1LMU Munich, Germany.
Understanding conditional statements requires more than just coherence. This study shows that probabilistic relevance, not just discourse coherence, is essential for asserting conditionals, challenging pragmatic explanations for their oddity.
Area of Science:
- Cognitive Science
- Linguistics
- Philosophy of Language
Background:
- Reasoning with conditional statements is fundamental to human cognition.
- The interpretation of conditionals, especially 'missing-link' examples, is debated.
- Existing theories often attribute oddities in conditionals to pragmatic factors.
Purpose of the Study:
- To investigate the role of connection in conditional statements.
- To disentangle discourse coherence from probabilistic relevance.
- To test whether discourse coherence alone is sufficient for assertability.
Main Methods:
- Experimental study design.
- Manipulation of discourse coherence and probabilistic relevance.
- Assessment of conditional assertability.
Main Results:
- Mere discourse coherence is insufficient for making conditionals assertable.
- Probabilistic relevance plays a crucial role in the acceptance of conditionals.
- Findings challenge pragmatic accounts that rely solely on coherence.
Conclusions:
- Conditional statements require a stronger connection than mere discourse coherence.
- Probabilistic relevance is a key factor in understanding and asserting conditionals.
- This research provides empirical evidence for the importance of connection in conditional reasoning.
Related Concept Videos
Theory of Attribution I: Correspondent Inference Theory
Criteria for Causality: Bradford Hill Criteria - II
Correlation and Causation
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Criteria for Causality: Bradford Hill Criteria - I
Contingency Table
Probability in Statistics
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...

