Journal of Data Science

Although hypothesis testing has been misused and abused, we argue that it remains an important method of inference. Requiring preregistration of the details of the inferences planned for a study is a major step to preventing abuse. But when doing hypothesis testing, in practice the null hypothesis is almost always taken to be a “point null”, that is, a hypothesis that a parameter is equal to a constant. One reason for this is that it makes the required computations easier, but with modern computer power this is no longer a compelling justification. In this note we explore the interval null hypothesis that the parameter lies in a fixed interval. We consider a specific example in detail.