| Title |
The effect of iconicity of visual displays on statistical reasoning: evidence in favor of the null hypothesis
|
|---|---|
| Published in |
Psychonomic Bulletin & Review, December 2013
|
| DOI | 10.3758/s13423-013-0555-4 |
| Pubmed ID | |
| Authors |
Miroslav Sirota, Lenka Kostovičová, Marie Juanchich |
| Abstract |
Knowing which properties of visual displays facilitate statistical reasoning bears practical and theoretical implications. Therefore, we studied the effect of one property of visual diplays - iconicity (i.e., the resemblance of a visual sign to its referent) - on Bayesian reasoning. Two main accounts of statistical reasoning predict different effect of iconicity on Bayesian reasoning. The ecological-rationality account predicts a positive iconicity effect, because more highly iconic signs resemble more individuated objects, which tap better into an evolutionary-designed frequency-coding mechanism that, in turn, facilitates Bayesian reasoning. The nested-sets account predicts a null iconicity effect, because iconicity does not affect the salience of a nested-sets structure-the factor facilitating Bayesian reasoning processed by a general reasoning mechanism. In two well-powered experiments (N = 577), we found no support for a positive iconicity effect across different iconicity levels that were manipulated in different visual displays (meta-analytical overall effect: log OR = -0.13, 95 % CI [-0.53, 0.28]). A Bayes factor analysis provided strong evidence in favor of the null hypothesis-the null iconicity effect. Thus, these findings corroborate the nested-sets rather than the ecological-rationality account of statistical reasoning. |
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| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 3% |
| Chile | 1 | 3% |
| Italy | 1 | 3% |
| United Kingdom | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 33 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 18% |
| Researcher | 5 | 13% |
| Student > Doctoral Student | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Lecturer | 3 | 8% |
| Other | 11 | 29% |
| Unknown | 6 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 22 | 58% |
| Business, Management and Accounting | 3 | 8% |
| Agricultural and Biological Sciences | 2 | 5% |
| Mathematics | 2 | 5% |
| Engineering | 2 | 5% |
| Other | 1 | 3% |
| Unknown | 6 | 16% |