On the Utility of Hypothesis Testing and the Principle of Parsimony

Recently, the argument has been made that “what is called testing may have its place in inference […], but it actually is just one way of describing one’s belief with respect to the possible values of a parameter. Instead, we recommend estimation of the full posterior distribution […].” (Tendeiro & Kiers, 2019). In this talk, I will argue why I believe in many cases statistical testing is a necessary precursor to parameter estimation. I will structure my talk along two main arguments: (1) the principle of parsimony; (2) the size of the effect depending on the specifics of the experimental set-up.