From the beginning of the most introductory statistics course, the declaration of a null and alternative hypothesis is the "first step" of any good experiment and subsequent analysis. Now that I have been venturing into more complex courses and topics, I see this exercise still being performed. I have always perceived the proposal of the null v. alternative as a teachable example of how to think of a study or experiment rather than a necessity (once you have an understanding of hypothesis testing and experimental design).
Do statisticians consistently propose a null and alternative in practice for all tests they perform? Is this common practice in the field or within a company? Or rather is it a "mental" heuristic when approaching statistical testing?
From my time doing experiments in biological research, we have always had a hypothesis to guide and motivate an experiment, but there was never the clear definition of a null and alternative. Is this an example of lack of scientific rigor?
Sorry for the naiveté of question as I am not a statistician.