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      The Origins of Religious Disbelief: A Dual Inheritance Approach

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          Abstract

          Widespread religious disbelief represents a key testing ground for theories of religion. We evaluated the predictions of three prominent theoretical approaches—secularization, cognitive byproduct, and dual inheritance—in a nationally representative (United States, N = 1,417) data set with preregistered analyses and found considerable support for the dual inheritance perspective. Of key predictors of religious disbelief, witnessing fewer credible cultural cues of religious commitment was the most potent, β = .28, followed distantly by reflective cognitive style, β = .13, and less advanced mentalizing, β = .05. Low cultural exposure predicted about 90% higher odds of atheism than did peak cognitive reflection, and cognitive reflection only predicted disbelief among those relatively low in cultural exposure to religion. This highlights the utility of considering both evolved intuitions and transmitted culture and emphasizes the dual roles of content- and context-biased social learning in the cultural transmission of disbelief (preprint https://psyarxiv.com/e29rt/ ).

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          Most cited references41

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          Bayesian estimation supersedes the t test.

          Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional t tests) when certainty in the estimate is high (unlike Bayesian model comparison using Bayes factors). The method also yields precise estimates of statistical power for various research goals. The software and programs are free and run on Macintosh, Windows, and Linux platforms. PsycINFO Database Record (c) 2013 APA, all rights reserved.
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            Assessing miserly information processing: An expansion of the Cognitive Reflection Test

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              Robust misinterpretation of confidence intervals.

              Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more useful alternative to NHST, and their use is strongly encouraged in the APA Manual. Nevertheless, little is known about how researchers interpret CIs. In this study, 120 researchers and 442 students-all in the field of psychology-were asked to assess the truth value of six particular statements involving different interpretations of a CI. Although all six statements were false, both researchers and students endorsed, on average, more than three statements, indicating a gross misunderstanding of CIs. Self-declared experience with statistics was not related to researchers' performance, and, even more surprisingly, researchers hardly outperformed the students, even though the students had not received any education on statistical inference whatsoever. Our findings suggest that many researchers do not know the correct interpretation of a CI. The misunderstandings surrounding p-values and CIs are particularly unfortunate because they constitute the main tools by which psychologists draw conclusions from data.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Social Psychological and Personality Science
                Social Psychological and Personality Science
                SAGE Publications
                1948-5506
                1948-5514
                September 2021
                March 05 2021
                September 2021
                : 12
                : 7
                : 1369-1379
                Affiliations
                [1 ]Centre for Culture and Evolution, Brunel University London, Uxbridge, United Kingdom
                [2 ]University of Kentucky, Lexington, KY, USA
                [3 ]University of Virginia, Charlottesville, VA, USA
                Article
                10.1177/1948550621994001
                4522bdf3-b1f8-4485-9ead-2e4b1bd1252c
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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