Schmid College of Science and Technology, Chapman University, 1 University Dr., Orange, CA 92866, USA
Department of Biology, McMaster University, 1280 Main St W, Hamilton, ON L8S 4L8, Canada.
J Exp Biol. 2020 Oct 12;223(Pt 19):jeb231894. doi: 10.1242/jeb.231894.
A powerful way to evaluate scientific explanations (hypotheses) is to test the predictions that they make. In this way, predictions serve as an important bridge between abstract hypotheses and concrete experiments. Experimental biologists, however, generally receive little guidance on how to generate quality predictions. Here, we identify two important components of good predictions - criticality and persuasiveness - which relate to the ability of a prediction (and the experiment it implies) to disprove a hypothesis or to convince a skeptic that the hypothesis has merit. Using a detailed example, we demonstrate how striving for predictions that are both critical and persuasive can speed scientific progress by leading us to more powerful experiments. Finally, we provide a quality control checklist to assist students and researchers as they navigate the hypothetico-deductive method from puzzling observations to experimental tests.
评估科学解释(假说)的一种有力方法是检验它们所做出的预测。通过这种方式,预测作为抽象假说和具体实验之间的重要桥梁。然而,实验生物学家通常在如何生成高质量的预测方面得到的指导很少。在这里,我们确定了好的预测的两个重要组成部分——关键性和说服力——这与预测(以及它所暗示的实验)反驳假说或说服怀疑论者相信该假说有价值的能力有关。我们使用一个详细的例子来说明,通过努力追求具有关键性和说服力的预测,我们可以通过引导我们进行更有力的实验来加速科学进步。最后,我们提供了一个质量控制清单,以帮助学生和研究人员在从令人困惑的观察到实验测试的假说演绎方法中进行导航。