When analyzing the results of an experiment, the mental focus on a specific hypothesis might prevent the exploration of other aspects of the data, effectively blinding one to new ideas. To test this notion, we performed an experiment in which we asked undergraduate students to analyze a fictitious dataset. In addition to being asked what they could conclude from the dataset, half of the students were asked to also test specific hypotheses. In line with our notion, students in the hypothesis-free group were almost 5 times more likely to observe an image of a gorilla when simply plotting the data, a proxy for an initial step towards data analysis. If these findings are representative also of scientific research as a whole, they warrant concern about the current emphasis on hypothesis-driven research, especially in the context of information-rich datasets such as those now routinely created in the biological sciences. Our work provides evidence for a link between the psychological effect of selective attention and hypothesis-driven data analysis, and suggests a hidden cost to having a hypothesis when analyzing a dataset.

中文翻译：

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在假设驱动的数据分析中的选择性注意

在分析实验结果时，将注意力集中在特定的假设上可能会阻止探索数据的其他方面，从而有效地使人们对新的想法视而不见。为了验证这一概念，我们进行了一项实验，要求大学生分析虚拟数据集。除了被问到他们可以从数据集中得出什么结论外，还要求一半的学生也测试特定的假设。与我们的观点一致，无假设组的学生在简单地绘制数据时观察大猩猩图像的可能性几乎高出5倍，这是迈向数据分析的第一步。如果这些发现在整个科学研究中也具有代表性，那么它们值得关注当前对假设驱动研究的重视，尤其是在信息丰富的数据集（例如现在在生物科学中常规创建的数据集）的背景下。我们的工作为选择性注意的心理影响与假设驱动的数据分析之间的联系提供了证据，并提出了在分析数据集时假设的隐性成本。