AI Article Synopsis
- Many professionals misunderstand p-values, which can lead to poor decision-making and affect the quality of research interventions.
- A survey of 164 academic psychologists revealed that many struggled to correctly interpret p-values, particularly with common misconceptions like the inverse probability and replication fallacies.
- The study emphasizes the need for better statistical education among researchers and proposes recommendations to enhance their understanding of statistical concepts.
Article Abstract
Common misconceptions of p-values are based on certain beliefs and attributions about the significance of the results. Thus, they affect the professionals' decisions and jeopardize the quality of interventions and the accumulation of valid scientific knowledge. We conducted a survey on 164 academic psychologists (134 Italian, 30 Chilean) questioned on this topic. Our findings are consistent with previous research and suggest that some participants do not know how to correctly interpret p-values. The inverse probability fallacy presents the greatest comprehension problems, followed by the replication fallacy. These results highlight the importance of the statistical re-education of researchers. Recommendations for improving statistical cognition are proposed.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4993781 | PMC |
| http://dx.doi.org/10.3389/fpsyg.2016.01247 | DOI Listing |
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