Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Many Reasons or Just One: How Response Mode Affects Reasoning in the Conjunction Problem

Many Reasons or Just One: How Response Mode Affects Reasoning in the Conjunction Problem Forty years of experimentation on class inclusion and its probabilistic relatives have led to inconsistent results and conclusions about human reasoning. Recent research on the conjunction “fallacy” recapitulates this history. In contrast to previous results, we found that a majority of participants adhere to class inclusion in the classic Linda problem. We outline a theoretical framework that attributes the contradictory results to differences in statistical sophistication and to differences in response mode—whether participants are asked for probability estimates or ranks—and propose two precise cognitive algorithms for ranking probabilities. Our framework allows us to make novel predictions about when and why people adhere to class inclusion. Evidence obtained in several studies supports these predictions and demonstrates that the proposed ranking algorithms can account for about three-quarters of participants' inferences in the Linda problem. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Thinking & Reasoning Taylor & Francis

Many Reasons or Just One: How Response Mode Affects Reasoning in the Conjunction Problem

Thinking & Reasoning , Volume 4 (4): 34 – Nov 1, 1998
34 pages

Loading next page...
 
/lp/taylor-francis/many-reasons-or-just-one-how-response-mode-affects-reasoning-in-the-kD4DL86Sjp

References (80)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1464-0708
eISSN
1354-6783
DOI
10.1080/135467898394102
Publisher site
See Article on Publisher Site

Abstract

Forty years of experimentation on class inclusion and its probabilistic relatives have led to inconsistent results and conclusions about human reasoning. Recent research on the conjunction “fallacy” recapitulates this history. In contrast to previous results, we found that a majority of participants adhere to class inclusion in the classic Linda problem. We outline a theoretical framework that attributes the contradictory results to differences in statistical sophistication and to differences in response mode—whether participants are asked for probability estimates or ranks—and propose two precise cognitive algorithms for ranking probabilities. Our framework allows us to make novel predictions about when and why people adhere to class inclusion. Evidence obtained in several studies supports these predictions and demonstrates that the proposed ranking algorithms can account for about three-quarters of participants' inferences in the Linda problem.

Journal

Thinking & ReasoningTaylor & Francis

Published: Nov 1, 1998

There are no references for this article.