The best predictions in experimental biology are critical and persuasive

Abstract

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.

Keywords: Experimental design; Hypothesis testing; Scientific method.